* use device agnostic APIs in test cases
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
* fix style
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
* add one more
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* xpu now supports integer device id, aligning to CUDA behaviors
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
* update to use device_properties
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
* fix style
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
* update comment
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
* fix comments
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
* fix style
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
---------
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* stash commit
* Experiment 1: Try just Gemma
* Experiment 1: Just try Gemma
* make fixup
* Trigger tests
* stash commit
* Try adding Gemma3 as well
* make fixup
* Correct attrib names
* Correct pipeline model mapping
* Add in all_model_classes for Gemma1 again
* Move the pipeline model mapping around again
* make fixup
* Revert Gemma3 changes since it's a VLM
* Let's try Falcon
* Correct attributes
* Correct attributes
* Let's try just overriding get_config() for now
* Do Nemotron too
* And Llama!
* Do llama/persimmon
* Correctly skip tests
* Fix Persimmon
* Include Phimoe
* Fix Gemma2
* Set model_tester_class correctly
* Add GLM
* More models!
* models models models
* make fixup
* Add Qwen3 + Qwen3MoE
* Correct import
* make fixup
* Add the QuestionAnswering classes
* Add the QuestionAnswering classes
* Move pipeline mapping to the right place
* Jetmoe too
* Stop RoPE testing models with no RoPE
* Fix up JetMOE a bit
* Fix up JetMOE a bit
* Can we just force pad_token_id all the time?
* make fixup
* fix starcoder2
* Move pipeline mapping
* Fix RoPE skipping
* Fix RecurrentGemma tests
* Fix Falcon tests
* Add MoE attributes
* Fix values for RoPE testing
* Make sure we set bos_token_id and eos_token_id in an appropriate range
* make fixup
* Fix GLM4
* Add mamba attributes
* Revert bits of JetMOE
* Re-add the JetMOE skips
* Update tests/causal_lm_tester.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Add licence
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Get parallel loader working. Include tests.
* Update the tests for parallel loading
* Rename env variables.
* Add docs for parallel model weight loading.
* Touch up parallel model loading docs.
* Touch up parallel model loading docs again.
* Edit comment in test_modeling_utils_parallel_loading.py
* Make sure HF_PARALLEL_LOADING_WORKERS is spelled correctly in modeling_utils.py
* Correct times for parallelized loading, previous times were for a "hot" filesystem
* Update parallel model loading so the spawn method is encapsulated. DRY up the code by leveraging get_submodule.
* Update docs on model loading parallelism so that details on setting the multiprocessing start method are removed, now that the package handles this step internally.
* Fix style on model loading parallelism changes.
* Merge latest version of master's modeling_utils.
* Removed unused variable.
* Fix argument packing for the parallel loader.
* Fix state dict being undefined in the parallel model loader.
* Rename variables used in parallel model loading for clarity. Use get_module_from_name().
* Switch to the use of threads for parallel model loading.
* Update docs for parallel loading.
* Remove the use of json.loads when evaluating HF_ENABLE_PARALLEL_LOADING. Prefer simple casting.
* Move parallelized shard loading into its own function.
* Remove use of is_true(). Favor checking env var true values for HF_ENABLE_PARALLEL_LOADING.
* Update copyright to 2025 in readme for paralell model loading.
* Remove garbage collection line in load_shard_file, implicit garbage collection already occurs.
* Run formatter on modeling_utils.py
* Apply style fixes
* Delete tests/utils/test_modeling_utils_parallel_loading.py
---------
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Co-authored-by: Cyril Vallez <cyril.vallez@huggingface.co>
* stash for now
* initial commit
* small updated
* up
* up
* works!
* nits and fixes
* don't loop too much
* finish working example
* update
* fix the small freeblocks issue
* feat: stream inputs to continuous batch
* fix: update attn from `eager` to `sdpa`
* refactor: fmt
* refactor: cleanup unnecessary code
* feat: add `update` fn to `PagedAttentionCache`
* feat: broken optimal block size computation
* fix: debugging invalid cache logic
* fix: attention mask
* refactor: use custom prompts for example
* feat: add streaming output
* fix: prefill split
refactor: add doc strings and unsound/redundant logic
fix: compute optimal blocks logic
* fix: send decoded tokens when `prefilling_split` -> `decoding`
* refactor: move logic to appropriate parent class
* fix: remove truncation as we split prefilling anyways
refactor: early return when we have enough selected requests
* feat: add paged attention forward
* push Ggraoh>
* add paged sdpa
* update
* btter mps defaults
* feat: add progress bar for `generate_batch`
* feat: add opentelemetry metrics (ttft + batch fill %age)
* feat: add tracing
* Add cuda graphs (#38059)
* draft cudagraphs addition
* nits
* styling
* update
* fix
* kinda draft of what it should look like
* fixes
* lol
* not sure why inf everywhere
* can generate but output is shit
* some fixes
* we should have a single device synch
* broken outputs but it does run
* refactor
* updates
* updates with some fixes
* fix mask causality
* another commit that casts after
* add error
* simplify example
* update
* updates
* revert llama changes
* fix merge conflicts
* fix: tracing and metrics
* my updates
* update script default values
* fix block allocation issue
* fix prefill split attnetion mask
* no bugs
* add paged eager
* fix
* update
* style
* feat: add pytorch traces
* fix
* fix
* refactor: remove pytorch profiler data
* style
* nits
* cleanup
* draft test file
* fix
* fix
* fix paged and graphs
* small renamings
* cleanups and push
* refactor: move tracing and metrics logic to utils
* refactor: trace more blocks of code
* nits
* nits
* update
* to profile or not to profile
* refactor: create new output object
* causal by default
* cleanup but generations are still off for IDK what reason
* simplifications but not running still
* this does work.
* small quality of life updates
* nits
* updaet
* fix the scheduler
* fix warning
* ol
* fully fixed
* nits
* different generation parameters
* nice
* just style
* feat: add cache memory usage
* feat: add kv cache free memory
* feat: add active/waiting count & req latency
* do the sampling
* fix: synchronize CUDA only if available and improve error handling in ContinuousBatchingManager
* fix on mps
* feat: add dashboard & histogram buckets
* perf: improve waiting reqs data structures
* attempt to compile, but we should only do it on mps AFAIK
* feat: decouple scheduling logic
* just a draft
* c;eanup and fixup
* optional
* style
* update
* update
* remove the draft documentation
* fix import as well
* update
* fix the test
* style doomed
---------
Co-authored-by: Luc Georges <luc.sydney.georges@gmail.com>
* starting attn refactor for encoder decoder models via bart (eager + sdpa)
* flash attention works, remove unnecessary code
* flex attention support for bart!, gotta check if the renaming is not too aggressive
* some comments
* skip flex grad test for standalone as done with the other test
* revert flex attn rename (for now), sdpa simplify, and todos
* more todos
* refactor mask creation for reuse
* modular attempt at biogpt
* first batch of other models
* fix attn dropout
* fix autoformer copies
* hubert
* another batch of models
* copies/style + last round of bart models --> whisper next?
* remove unnecessary _reshape function and remove copy to whisper
* add skip for decoder-only models out of enc-dec (same as in bart)
* bring back licences
* remove comment, added to pr read instead
* mostly docs
* disable sew flex attn as it's unclear attn mask for now
* oops
* test fixes for enc-dec
* torch fx fixes + try at flex attn
* skip on mbart
* some more fixes
* musicgen skip / delete old attn class logic + sdpa compose compile skip
* disable flex attn for musicgen, not worth the effort
* more fixes and style
* flex attention test for dropout and encoder decoder that dont have main input names
* informer fixes
* the weirdest thing I've encountered yet...
* style
* remove empty tensor attempt, found core root in previous commits
* disable time series due to tests being very text centric on inputs
* add speech to text to be ignoring the other attns, also due to tests
* update docs
* remaining issues resolved ?
* update docs for current state --> nllb moe and pegasus x sdpa is questionable :D
* some models have not set the is_causal flag...
* change dtype in softmax tol old behaviour + some modular fixes
* I hate it but it is what it is
* fixes from main for bart
* forgot this one
* some model fixes
* style
* current status
* marian works now
* fixing some copies
* some copy fixes + time series x informer
* last models possibly and fixes on style/copies
* some post merge fixes
* more fixes
* make attention interface callable and move warnings there
* style lol
* add comment to "unsupported"
* remove callable interface and change interface warnings + some copies
* fix
* ternary is ugly af, make it simpler
* how did that happen
* fix flex attn test
* failing the test
* no more fallback! fixing copies next
* style + attn fixed
* fixing copies and mask creation
* wrong copy
* fixup tests and disable flex attn for now
* fixup last tests?
* _get_padding_size module
* do not patchify images when processing multi image
* modify llava onevision image processor fast
* tensor to list of tensors
* backward compat
* reuse pad_to_square in llave & some clarification
* add to doc
* fix: consider no image cases (text only or video)
* add integration test
* style & repo_consistency
* add seq_idx and fa kwargs
* update tests
* docs and grad ckpt support
* fmt
* better names
* test_raise_missing_padding_free_kwarg_errs
* + seq_idx in doc strings
* padding free training docs
* add link to pr plots
* raise err on attn_mask with padding free
* rm raising missing padding free err test
* BambaFlashAttentionKwargs
* run modular util for modular_granitemoehybrid.py
bnb quant tests: remove obsolete trust_remote_code test
The MPT model is now natively integrated in Transformers and no longer requires trust_remote_code=True. This removes the failing test_get_keys_to_not_convert_trust_remote_code and related usage, which depended on remote code and caused CI issues due to missing dependencies (e.g., triton_pre_mlir).
* fix sliding attn
* make style
* Update tests/test_modeling_common.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* no a second throught, should default to `True` fo BC
---------
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* use device agnostic APIs in tests
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
* more
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
* fix style
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
* add reset_peak_memory_stats API
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* update
---------
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* pipeline generation defaults
* add max_new_tokens=20 in test pipelines
* pop all kwargs that are used to parameterize generation config
* add class attr that tell us whether a pipeline calls generate
* tmp commit
* pt text gen pipeline tests passing
* remove failing tf tests
* fix text gen pipeline mixin test corner case
* update text_to_audio pipeline tests
* trigger tests
* a few more tests
* skips
* some more audio tests
* not slow
* broken
* lower severity of generation mode errors
* fix all asr pipeline tests
* nit
* skip
* image to text pipeline tests
* text2test pipeline
* last pipelines
* fix flaky
* PR comments
* handle generate attrs more carefully in models that cant generate
* same as above
* tmp commit (imports broken)
* working version; update tests
* remove line break
* shorter msg
* dola checks need num_beams=1; other minor PR comments
* update early trainer failing on bad gen config
* make fixup
* test msg
* add args support to fast image processors
* add comment for clarity
* fix-copies
* Handle child class args passed as both args or kwargs in call and preprocess functions
* revert support args passed as kwargs in overwritten preprocess
* fix image processor errors
* Add flash-attention-2 backend for ESM-2
Signed-off-by: Peter St. John <pstjohn@nvidia.com>
* update extended_attention_mask for fa2
Signed-off-by: Peter St. John <pstjohn@nvidia.com>
* add test_flash_attn_2_equivalence test
Signed-off-by: Peter St. John <pstjohn@nvidia.com>
---------
Signed-off-by: Peter St. John <pstjohn@nvidia.com>
* Include output embedding as well with `include_embedding` flag
Summary:
att
Test Plan:
python tests/quantization/torchao_integration/test_torchao.py -k test_include_embedding
Reviewers:
Subscribers:
Tasks:
Tags:
* format
* rename include_embedding to include_input_output_embeddings
---------
Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com>
* enable trainer test cases on xpu
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
* fix style
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
---------
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
* mvp
* remove trust_remote_code
* generate_from_hub
* handle requirements; docs
* english
* doc PR suggestions
* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* changed remote code path to generate/generate.py
* model repo has custom generate -> override base generate
* check for proper inheritance
* some doc updates (missing: tag-related docs)
* update docs to model repo
* nit
* nit
* nits
* Update src/transformers/dynamic_module_utils.py
* Apply suggestions from code review
* Update docs/source/en/generation_strategies.md
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* trust remote code is required
* use new import utils for requirements version parsing
* use org examples
* add tests
* Apply suggestions from code review
Co-authored-by: Manuel de Prada Corral <6536835+manueldeprada@users.noreply.github.com>
* ascii file structure; tag instructions on readme.md
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: Manuel de Prada Corral <6536835+manueldeprada@users.noreply.github.com>
* enable csm test cases on XPU, all passed
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
* fix style
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
---------
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
* enable finegrained_fp8 cases on XPU
Signed-off-by: Yao Matrix <matrix.yao@intel.com>
* fix style
Signed-off-by: Yao Matrix <matrix.yao@intel.com>
* change back to auto
Signed-off-by: Yao Matrix <matrix.yao@intel.com>
* rename per comments
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
---------
Signed-off-by: Yao Matrix <matrix.yao@intel.com>
Signed-off-by: Matrix Yao <matrix.yao@intel.com>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* init vilt image processor fast
* Refactor image processor tests to use loop for all processors
* Add ViltImageProcessorFast with PyTorch-based optimized image processing
* Change made automatically by make fixup command
* Change made automatically by make fix-copies command
* Fix type hints in ViltImageProcessorFast for Python compatibility
* Define constants for image resizing based on COCO dataset aspect ratio
* Add missing property initializations to ViltImageProcessorFast
* Extract resize logic into dedicated method in ViltImageProcessorFast
* Extract padding logic into dedicated method
* Implement shape-based image grouping for optimized processing in Vilt
* Update test suite to verify ViltImageProcessorFast attributes
* Move variable declarations to _preprocess method parameters
* Remove unused parameters
* Rename _resize method to resize to override existing function
* Remove whitespace
* Remove unnecessary type check and conversion for stacked_images
* Remove redundant loop and apply padding directly to stacked images
* Refactor pad function to return images and mask as tuple instead of dict
* Add tests comparing padding masks in slow and fast implementations
* Update ViltImageProcessor tests to ensure compatibility between slow and fast implementations
* Replace add_start_docstrings with auto_docstring in ViltImageProcessorFast
* Move docstrings of custom args to ViltFastImageProcessorKwargs
* Use reorder_images function for both masks and images
---------
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* fix llava processor to calculate unpad size correctly
* repo consistency
* Revert "repo consistency" & "setUp in llava family"
This reverts commit 26a50af8db.
* add edge case test for padding & unpadding
* compute unpadding size from original size
* make test config explicit
* Revert "compute unpadding size from original size"
This reverts commit 752cd27ad9.
* Revert "add edge case test for padding & unpadding"
This reverts commit ccbd094d69.
* revert unpad logic
* remove irrelevant tests
* model test
* remove processor from model test
---------
Co-authored-by: jaycha <jaycha@ncsoft.com>
* initial design
* update all video processors
* add tests
* need to add qwen2-vl (not tested yet)
* add qwen2-vl in auto map
* fix copies
* isort
* resolve confilicts kinda
* nit:
* qwen2-vl is happy now
* qwen2-5 happy
* other models are happy
* fix copies
* fix tests
* add docs
* CI green now?
* add more tests
* even more changes + tests
* doc builder fail
* nit
* Update src/transformers/models/auto/processing_auto.py
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* small update
* imports correctly
* dump, otherwise this is getting unmanagebale T-T
* dump
* update
* another update
* update
* tests
* move
* modular
* docs
* test
* another update
* init
* remove flakiness in tests
* fixup
* clean up and remove commented lines
* docs
* skip this one!
* last fix after rebasing
* run fixup
* delete slow files
* remove unnecessary tests + clean up a bit
* small fixes
* fix tests
* more updates
* docs
* fix tests
* update
* style
* fix qwen2-5-vl
* fixup
* fixup
* unflatten batch when preparing
* dump, come back soon
* add docs and fix some tests
* how to guard this with new dummies?
* chat templates in qwen
* address some comments
* remove `Fast` suffix
* fixup
* oops should be imported from transforms
* typo in requires dummies
* new model added with video support
* fixup once more
* last fixup I hope
* revert image processor name + comments
* oh, this is why fetch test is failing
* fix tests
* fix more tests
* fixup
* add new models: internvl, smolvlm
* update docs
* imprt once
* fix failing tests
* do we need to guard it here again, why?
* new model was added, update it
* remove testcase from tester
* fix tests
* make style
* not related CI fail, lets' just fix here
* mark flaky for now, filas 15 out of 100
* style
* maybe we can do this way?
* don't download images in setup class
---------
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* enable generation fsdp/utils test cases on XPU
Signed-off-by: Yao Matrix <matrix.yao@intel.com>
* fix style
Signed-off-by: Yao Matrix <matrix.yao@intel.com>
* xx
Signed-off-by: Yao Matrix <matrix.yao@intel.com>
* use backend_xx APIs
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>
* update models
* why rename
* return attn weights when sdpa
* fixes
* fix attn implementation composite
* fix moshi
* add message
* add typings
* use explicitly all flags for each attn type
* fix some tests
* import what is needed
* kosmos on main has ew attention already, yay
* new models in main, run fixup
* won't fix kosmos yet
* fix-copies
* clean up after rebasing
* fix tests
* style
* dont cast attns to fp32
* did we update ruff? oke, let's just do what it asks
* fix pixtral after rebase
* Add fast image processor support for Swin2SR
* Add Swin2SR tests of fast image processing
* Update docs and remove unnecessary test func
* Fix docstring formatting
* Skip fast vs slow processing test
---------
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* i guessreverted all CdGen classes
* style
* llava onevision
* fix copies
* fix some tests
* some more tests
* dump
* skip these
* nevermind, i am dumb
* revert fix not needed
* fixup
* fixup
* another fixup
* more fixup to make ci finally happy
* fixup after rebasing
* fix qwen tests
* add internVL + typos here and there
* image token index -> id
* style
* fix init weights
* revert blip-2 not supported
* address comments
* fix copies
* revert blip2 test file as well
* as discussed internally, revert back CdGen models
* fix some tests
* fix more tests for compile
* CI red
* fix copies
* enumerate explicitly allowed models
* address comments
* fix tests
* fixup
* style again
* add tests for new model class
* another fixup ( x _ x )
* [fixup] unused attributes can be removed post-deprecation
* Enable granite speech 3.3 tests
* skip sdpa test for granite speech
* Explicitly move model to device
* Use granite speech 2b in tests
---------
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
* args keep_torch_compile=False in _save and _wwrap_method
* Fix FSDP execution on evaluation for torch_compile mode
* add test trainer FSDP + Torch Compile
* fix quality code
* make style
* Revert " make style"
This reverts commit 77e797f8829c50992cc21496be3d9a3e480e1c97.
* make style
* enable xpu in test_trainer
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* fix style
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* enhance _device_agnostic_dispatch to cover value
Signed-off-by: Yao Matrix <matrix.yao@intel.com>
* add default values for torch not available case
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
---------
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
Signed-off-by: Yao Matrix <matrix.yao@intel.com>
* [fix] one pixel should be added when length is odd
* [fix] add vision_aspect_ratio args & typo
* [fix] style
* [fix] do not fix fast file directly
* [fix] convert using modular
* remove duplicate codes
* match unpad logic with pad logic
* test odd-sized images for llava & aria
* test unpad odd-sized padding for llava family
* fix style
* add kwarg to onvision modular
* move vision_aspect_ratio from image_processor to processor
(llava_onevision)
* rm already deprecated padding max length
* truncate_strategy AS AN ARG is already deprecated for a few years
* fix
* rm test_padding_to_max_length
* rm pad_to_max_length=True in other tests
* rm from common
* missed fnet
* Support `AOPerModuleConfig` and include_embedding
Summary:
This PR adds support per module configuration for torchao
Also added per module quantization examples:
1. Quantizing different layers with different quantization configs
2. Skip quantization for certain layers
Test Plan:
python tests/quantization/torchao_integration/test_torchao.py -k test_include_embedding
python tests/quantization/torchao_integration/test_torchao.py -k test_per_module_config_skip
Reviewers:
Subscribers:
Tasks:
Tags:
* format
* format
* inlcude embedding remove input embedding from module not to convert
* more docs
* Update docs/source/en/quantization/torchao.md
Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com>
* Update src/transformers/quantizers/quantizer_torchao.py
Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com>
* Update src/transformers/quantizers/quantizer_torchao.py
Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com>
---------
Co-authored-by: Mohamed Mekkouri <93391238+MekkCyber@users.noreply.github.com>
* enable internvl UTs on XPU
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* fix style
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* fix style per comments
Signed-off-by: Yao Matrix <matrix.yao@intel.com>
---------
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
Signed-off-by: Yao Matrix <matrix.yao@intel.com>
* copy the last changes from broken PR
* small format
* some fixes and refactoring after review
* format
* add config attr for loss
* some fixes and refactoring
* fix copies
* fix style
* add test for d-fine resnet
* fix decoder layer prop
* fix dummies
* format init
* remove extra print
* refactor modeling, move resnet into separate folder
* fix resnet config
* change resnet on hgnet_v2, add clamp into decoder
* fix init
* fix config doc
* fix init
* fix dummies
* fix config docs
* fix hgnet_v2 config typo
* format modular
* add image classification for hgnet, some refactoring
* format tests
* fix dummies
* fix init
* fix style
* fix init for hgnet v2
* fix index.md, add init rnage for hgnet
* fix conversion
* add missing attr to encoder
* add loss for d-fine, add additional output for rt-detr decoder
* tests and docs fixes
* fix rt_detr v2 conversion
* some fixes for loos and decoder output
* some fixes for loss
* small fix for converted modeling
* add n model config, some todo comments for modular
* convert script adjustments and fixes, small refact
* remove extra output for rt_detr
* make some outputs optionsl, fix conversion
* some posr merge fixes
* small fix
* last field fix
* fix not split for hgnet_v2
* disable parallelism test for hgnet_v2 image classification
* skip multi gpu for d-fine
* adjust after merge init
* remove extra comment
* fix repo name references
* small fixes for tests
* Fix checkpoint path
* Fix consistency
* Fixing docs
---------
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* added fast image processor for VitMatte including updated and new tests, fixed a bug in the slow image processor that processed images incorrectly for input format ChannelDimension.FIRST in which case the trimaps were not added in the correct dimension, this bug was also reflected in the tests through incorretly shaped trimaps being passed
* final edits for fast vitmatte image processor and tests
* final edits for fast vitmatte image processor and tests
---------
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* added the configuartion for sam_hq
* added the modeelling for sam_hq
* added the sam hq mask decoder with hq features
* added the code for the samhq
* added the code for the samhq
* added the code for the samhq
* Delete src/transformers/models/sam_hq/modelling_sam_hq.py
* added the code for the samhq
* added the code for the samhq
* added the chnages for the modeelling
* added the code for sam hq for image processing
* added code for the sam hq model
* added the required changes
* added the changes
* added the key mappings for the sam hq
* adding the working code of samhq
* added the required files
* adding the pt object
* added the push to hub account
* added the args for the sam maks decoder
* added the args for the sam hq vision config
* aded the some more documentation
* removed the unecessary spaces
* all required chnages
* removed the image processor
* added the required file
* added the changes for the checkcopies
* added the code for modular file
* added the changes for the __init file
* added the code for the interm embeds
* added the code for sam hq
* added the changes for modular file
* added the test file
* added the changes required
* added the changes required
* added the code for the
* added the cl errors
* added the changes
* added the required changes
* added the some code
* added the code for the removing image processor
* added the test dimensins
* added the code for the removing extra used variables
* added the code for modeluar file hf_mlp for a better name
* removed abbrevaation in core functionality
* removed abbrevaation in core functionality
* .contiguous() method is often used to ensure that the tensor is stored in a contiguous block of memory
* added the code which is after make fixup
* added some test for the intermediate embeddings test
* added the code for the torch support in sam hq
* added the code for the updated modular file
* added the changes for documentations as mentioned
* removed the heading
* add the changes for the code
* first mentioned issue resolved
* added the changes code to processor
* added the easy loading to init file
* added the changes to code
* added the code to changes
* added the code to work
* added the code for sam hq
* added the code for sam hq
* added the code for the point pad value
* added the small test for the image embeddings and intermediate embedding
* added the code
* added the code
* added the code for the tests
* added the code
* added ythe code for the processor file
* added the code
* added the code
* added the code
* added the code
* added the code
* added the code for tests and some checks
* added some code
* added the code
* added the code
* added some code
* added some code
* added the changes for required
* added the code
* added the code
* added the code
* added the code
* added the code
* added the code
* added the code
* added the code
* added the code
* added the code
* added some changes
* added some changes
* removed spaces and quality checks
* added some code
* added some code
* added some code
* added code quality checks
* added the checks for quality checks
* addded some code which fixes test_inference_mask_generation_no_point
* added code for the test_inference_mask_generation_one_point_one_bb
* added code for the test_inference_mask_generation_one_point_one_bb_zero
* added code for the test_inference_mask_generation_one_box
* added some code in modelling for testing
* added some code which sort maks with high score
* added some code
* added some code
* added some code for the move KEYS_TO_MODIFY_MAPPING
* added some code for the unsqueeze removal
* added some code for the unsqueeze removal
* added some code
* added some code
* add some code
* added some code
* added some code
* added some testign values changed
* added changes to code in sam hq for readbility purpose
* added pre commit checks
* added the fix samvisionmodel for compatibilty
* added the changes made on sam by cyyever
* fixed the tests for samhq
* added some the code
* added some code related to init file issue during merge conflicts
* remobved the merge conflicts
* added changes mentioned by aruther and mobap
* added changes mentioned by aruther and mobap
* solving quality checks
* added the changes for input clearly
* added the changes
* added changes in mask generation file rgearding model inputs and sam hq quargs in processor file
* added changes in processor file
* added the Setup -> setupclass conversion
* added the code mentioned for processor
* added changes for the code
* added some code
* added some code
* added some code
---------
Co-authored-by: Pablo Montalvo <39954772+molbap@users.noreply.github.com>
Two PEFT tests are actually failing:
tests/peft_integration/test_peft_integration.py::PeftIntegrationTester::test_delete_adapter
tests/peft_integration/test_peft_integration.py::PeftIntegrationTester::test_peft_pipeline_no_warning
This must have been going on for some time but was apparently never
noticed. The cause is that the tests themselves are faulty, the PEFT
integration is correct in these cases.
test_delete_adapter
The first faulty test was introduced by #34650. AFAICT, it should never
have passed in the first place, the PEFT integration logic was not
changed in the meantime. At this point, the logs for the PR CI are gone,
so I'm not sure if the test passed back then or not.
test_peft_pipeline_no_warning
This test was introduced in #36783 and should also never have passed, as
the self.assertNoLogs context manager only returns None, thus the assert
should never have worked (mea culpa for suggesting this code snippet).
Here too, the CI logs are deleted by now, so I can't check if the test
already failed back then.
* Fix qwen2_5 get_rope_index tensor device locations
* simpler fix
* edit right file for modular model
* add a test
* try normalizing type to fix non-video
* fix some imports
* add a video forward test with dummy input
* skip compilation on cpu offload
* add test
* better logic
* docstring
* boolean logic
* add disk offload check
* warn users if compilation options are set but compilation doesn happen
* fix test
---------
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* update aria tests
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* add cuda tests
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* check outputs for cpu and cuda and xpu
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* check outputs for cpu and cuda and xpu
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* check outputs for cpu and cuda and xpu
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* check output for each device
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* fix style
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* fix style
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* fix xpu output
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* add comments and use assert list equal
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* rm pad token assign
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
---------
Signed-off-by: jiqing-feng <jiqing.feng@intel.com>
* fast image processor template for MobileNetV1 via transformers-cli
* Add fast image processors and unify tests for slow/fast image processor classes
* added loop over image_processor_list for all tests and removed boilerplate comments.
---------
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* support poolformer fast image processor
* support test for crop_pct=None
* run make style
* Apply suggestions from code review
* rename test
---------
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
* tokenize inputs directly in apply_chat_template
* refactor processing
* revert changes processing llava
* Update docs
* fix issue with str being iterable
* add test chat text only
* change function name
* enable blip2 and emu3 modeling cases on XPU
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* fix style
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* remove extra new line
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* update
---------
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* enable 6 granite cases on XPU
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* make them all pass on A100
Signed-off-by: N <matrix.yao@intel.com>
* fix style
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* update
---------
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
Signed-off-by: N <matrix.yao@intel.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* enable mllama testing on xpu
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* more mllama cases enabling
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* make cases pass on A100
Signed-off-by: N <matrix.yao@intel.com>
---------
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
Signed-off-by: N <matrix.yao@intel.com>
* fix: RecurrentGemma crashes during inference for inputs longer than sliding window width
* fix recurrentgemma tests; add long test bigger than context window
* [fix] make legacy bnb code work
* [fix] use get with default instead of getter
* add test for bnb 8bit optim skip embed
* [fix] style
* add require annotation of bnb
---------
Co-authored-by: jaycha <jaycha@ncsoft.com>
Co-authored-by: Marc Sun <57196510+SunMarc@users.noreply.github.com>
* fix: qwen2.5 omni modular get_rope_index
* test: add test for qwen2.5 omni rope index (video with audio input)
* style
* expected_position_ids readability
* fix: use spatial_merge_size = 1 in unit test
* initial commit
* add convert internvl
* add first end-to-end working internvl
* nit prompt and image proc
* add working chat template
* add conversion llama-based models
* add tests
* pass all tests
* fix isort
* fix modular after main merge
* add video processing for internvl
* add support for interlaced images and videos
* Remove processing and config from modular, add more tests
* add llama model tests
* Modify processor for compatibility with refactored got ocr image processor
* add comments in processor
* Add docs and nits
* change video processing to use custom sample_indices_fn
* rebase and fix tests
* add processor tests
* Add changes Raushan review
* Use the new attention interface for the vision model
* nits
* add support for custom video_load_backend
* remove mention to InternVLTokenizer
* refactor vision model to simplify logic
* refactor processor for better readibility
* fix copies
* fix require av processor test
* refactor internVL vision
* Update processor and fix processing tests
* fix docstring
* update convert_weights for internvl3
* change image processor to fast by default
* remove do_center_crop=True in convert_weights
* force use_cache to True
* push_to_hub before reloading
* fix internVLVision for larger models
* update convert weight for qk norm
* fix convert_weights
* fix eos_token_id in convert
* update docs and integration tests
* make modifs after review
* fix wrong k_norm and reduce modular
* change image_token_index to image_token_id
* change checkpoint to OpenGVLab org
* last nits
* explicitely del self.num_key_value_groups
* add extra special tokens
* use only `xxx_token_id` for multimodal tokens
* update modeling files as well
* fixup
* why fixup doesn't fix modular docstring first?
* janus, need to update configs in the hub still
* last fixup
