* adding model and conversion scripts
* add imports to test vjepa conversion
* fix imports and make conversion work
* fix computation for short side
* replace attention with library attention function
* cleanup more attention classes
* remove config overrides
* add test cases, fix some of the failing ones
* fix the model outputs
* fix outputs of the model per review
* fix too big model test case
* fix styling __init__.py
* fix initialization test
* remove all asserts per review
* update sorting unsorting logic as per feedback
* remove is_video per review
* remove another is_video segment
* remove unwanted stuff
* small fixes
* add docstrings for the model
* revert adding vjepa2 config here
* update styling
* add config docstrings (wip)
* fix dpr issue
* removed test failing issues
* update styles
* merge predictor configs into main config
* remove processing code, add video processor
* remove permute which is not necessary now
* fix styles
* updated vjepa2 to be in video_processing_auto
* update comment for preprocessing
* test integration test and fix the outputs
* update test values, change test to look at repeated frames for a given image
* add a simple video processing test
* refactoring pixel_values_videos and upload ckpts to original
* fix torch_fx test cases
* remove unused config
* add all config docstrings
* add more integration tests
* add basic doc
* revert unwanted styling changes
* working make fixup
* Fix model_type in config
* Add ForVideoClassification model
* update attention implementation to fit new hf standards
* fix the preprocessing logic, ensure it matches the original model
* remove use_rope logic, cleanup
* fix docstrings
* Further cleanup, update doc
* Fix model prefix
* fix get_vision_features
* VJEPA2Embeddings style refactor
* nit, style comment
* change modules default values
* Only `str` activation in config
* GradientCheckpointingLayer
* fixup
* fix conversion script
* Remove return_dict
* remove None return typehint
* Refactor VJEPA2Layer, remove use_SiLU
* Fix fx tests
* dpr -> drop_path_rates
* move *ModelOutput on top
* format docs bit
* update docs
* update docs
* update doc example
* remove prune_heads from model
* remove unused config params
* refactor embed signature
* Add vjepa to docs
* Fix config docstring
* attention head
* update defaults
* Update docs/source/en/model_doc/vjepa2.md
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update docs/source/en/model_doc/vjepa2.md
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Fix import
* Min refactoring
* Update HUB_SOURCE and HUB_REPO in conversion script
* Add missing headers
* VJEPA -> V-JEPA in docs
* Add image to doc
* fix style
* fix init weights
* change checkpoint name in modeling tests
* Initial cls head setup
* remove rop attention from head (not needed)
* remove swigluffn - not needed
* Add siglip layer
* Replace with siglip layer
* Rename Siglip - VJEPA2
* remove unused modules
* remove siglip mlp
* nit
* remove MLP
* Refactor head cross attention
* refactor VJEPA2HeadCrossAttentionLayer
* nit renaming
* fixup
* remove commented code
* Add cls head params to config
* depth from config
* move pooler + classifier to the model
* Update for cls model signature
* move layers, rename a bit
* fix docs
* update weights init
* remove typehint for init
* add to auto-mapping
* enable tests
* Add conversion script
* fixup
* add to docs
* fix docs
* nit
* refactor for mapping
* clean
* Add integration test
* Fixing multi gpu test
* update not-split-modules
* update video cls test tolerance
* Increase test_inference_image tolerance
* Update no-split modules for multi gpu
* Apply suggestions from code review
* fixing multi-gpu
* fix docstring
* Add cls snippet to docs
* Update checkpoint
* Refactor DBRX tests to use CausalLMModelTest base classes
- Changed DbrxModelTester to inherit from CausalLMModelTester
- Changed DbrxModelTest to inherit from CausalLMModelTest
- Removed duplicate methods that are already in base classes
- Added required class attributes for model classes
- Updated pipeline_model_mapping to include feature-extraction
- Kept DBRX-specific configuration and test methods
- Disabled RoPE tests as DBRX's rotary embedding doesn't accept config parameter
This refactoring reduces code duplication and follows the pattern established
in other causal LM model tests like Gemma.
* Apply style fixes
* Trigger tests
* Refactor DBRX test
* Make sure the DBRX-specific settings are handled
* Use the attribute_map
* Fix attribute map
---------
Co-authored-by: openhands <openhands@all-hands.dev>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
* Unbreak optimum-executorch
* use static cache if has layer_types but no sliding_window
* revert view on kv_arange
---------
Co-authored-by: Guang Yang <guangyang@fb.com>
* remove it from all py files
* remove it from the doc
* remove it from examples
* style
* remove traces of _fast_init
* Update test_peft_integration.py
* CIs
* apply updates smolVLM (still needs workaround for chat template)
* add other models
* dump qwen omni for now, come back later
* port qwen omni from their impl
* wait, all qwens sample videos in same way!
* clean up
* make smolvlm backwards compatible and fix padding
* dix some tests
* fox smolvlm tests
* more clean up and test fixing
* delete unused arg
* fix
* address comments
* style
* fix test
* adding model and conversion scripts
* add imports to test vjepa conversion
* fix imports and make conversion work
* fix computation for short side
* replace attention with library attention function
* cleanup more attention classes
* remove config overrides
* add test cases, fix some of the failing ones
* fix the model outputs
* fix outputs of the model per review
* fix too big model test case
* fix styling __init__.py
* fix initialization test
* remove all asserts per review
* update sorting unsorting logic as per feedback
* remove is_video per review
* remove another is_video segment
* remove unwanted stuff
* small fixes
* add docstrings for the model
* revert adding vjepa2 config here
* update styling
* add config docstrings (wip)
* fix dpr issue
* removed test failing issues
* update styles
* merge predictor configs into main config
* remove processing code, add video processor
* remove permute which is not necessary now
* fix styles
* updated vjepa2 to be in video_processing_auto
* update comment for preprocessing
* test integration test and fix the outputs
* update test values, change test to look at repeated frames for a given image
* add a simple video processing test
* refactoring pixel_values_videos and upload ckpts to original
* fix torch_fx test cases
* remove unused config
* add all config docstrings
* add more integration tests
* add basic doc
* revert unwanted styling changes
* working make fixup
* Fix model_type in config
* update attention implementation to fit new hf standards
* fix the preprocessing logic, ensure it matches the original model
* remove use_rope logic, cleanup
* fix docstrings
* Further cleanup, update doc
* Fix model prefix
* fix get_vision_features
* VJEPA2Embeddings style refactor
* nit, style comment
* change modules default values
* Only `str` activation in config
* GradientCheckpointingLayer
* fixup
* fix conversion script
* Remove return_dict
* remove None return typehint
* Refactor VJEPA2Layer, remove use_SiLU
* Fix fx tests
* dpr -> drop_path_rates
* move *ModelOutput on top
* format docs bit
* update docs
* update docs
* update doc example
* remove prune_heads from model
* remove unused config params
* refactor embed signature
* Add vjepa to docs
* Fix config docstring
* update defaults
* Update docs/source/en/model_doc/vjepa2.md
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Update docs/source/en/model_doc/vjepa2.md
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* Fix import
* Min refactoring
* Update HUB_SOURCE and HUB_REPO in conversion script
* Add missing headers
* VJEPA -> V-JEPA in docs
* Add image to doc
* fix style
* fix init weights
* change checkpoint name in modeling tests
---------
Co-authored-by: Koustuv Sinha <koustuv.sinha@mail.mcgill.ca>
Co-authored-by: yonigozlan <yoni.gozlan@huggingface.co>
Co-authored-by: Yoni Gozlan <74535834+yonigozlan@users.noreply.github.com>
Co-authored-by: Koustuv Sinha <koustuvsinha@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
* enable glm4 integration cases on XPU, set xpu expectation for blip2
Signed-off-by: Matrix YAO <matrix.yao@intel.com>
* more
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* fix style
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* refine wording
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* refine test case names
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* run
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* add gemma2 and chameleon
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* fix review comments
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
---------
Signed-off-by: Matrix YAO <matrix.yao@intel.com>
Signed-off-by: YAO Matrix <matrix.yao@intel.com>
* added fast image processor for ZoeDepth and expanded tests accordingly
* added fast image processor for ZoeDepth and expanded tests accordingly, hopefully fixed repo consistency issue too now
* final edits for zoedept fast image processor
* final minor edit for zoedepth fast imate procesor
Fix "RuntimeError: Expected all tensors to be on the same device,
but found at least two devices, cuda:0 and cpu" error running the
following roformer tests on GPUs (CUDA or XPU):
```
tests/models/roformer/test_modeling_roformer.py::RoFormerSinusoidalPositionalEmbeddingTest::test_basic
tests/models/roformer/test_modeling_roformer.py::RoFormerSelfAttentionRotaryPositionEmbeddingTest::test_apply_rotary_position_embeddings
```
Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com>
* Fix multiple devices error on Janus
* Fix AttributeError on Janus BOI token
* Initialize lm first in Janus to get correct device map
* Added expectations for Janus test_model_generate_images
* Fixed JanusVisionEncoderLayer being split across devices
* Code formatting
* Adding modeling file
* Reverted changes out of scope for this PR
* feat: add colqwen2 (wip)
* tests: fix test_attention_outputs
* tests: reduce hidden size to accelerate tests
* tests: fix `test_attention_outputs` 🥳
* fix: fix wrong parent class for `ColQwen2ForRetrievalOutput`
* fix: minor typing and style changes
* chore: run `make style`
* feat: remove redundant `max_num_visual_tokens` attribute in `ColQwen2Processor`
* tests: tweak comments
* style: apply ruff formatter
* feat: move default values for `visual_prompt_prefix` and `query_prefix`
* docs: update ColQwen2 model card
* docs: tweak model cards
* docs: add required example config checkpoint
* tests: update expected scores in integration test
* docs: tweak quickstart snippets
* fix: address PR comments
* tests: fix colqwen2 tests + tweak comment in colpali test
* tests: unskip useful tests
* fix: fix bug when `visual_prompt_prefix` or `query_prefix` is an empty string
* fix: fix ColPali outputs when `return_dict == False`
* fix: fix issue with PaliGemma output not being a dict
* docs: set default dtype to bfloat16 in quickstart snippets
* fix: fix error when `return_dict=False` in ColPali and ColQwen2
* tests: fix special tokens not being replaced in input_ids
* style: fix lint
* fix: `ColQwen2Processor`'s `padding_side` is now set from `processor_config.json`
* fix: remove unused `padding_side` in ColQwen2 model
* docs: update ColQwen2's model doc
* fix: fix harcoded vlm backbone class in ColQwen2Config
* fix: remove `padding_side` from ColQwen2Processor as should fed from kwargs
* docs: fix typo in model docstring
* docs: add illuin mention in model docs
* fix: let `padding_size` be handled by `tokenizer_config.json`
* docs: add colpali reference url in colqwen2's model doc
* docs: add Hf mention in model docs
* docs: add late interaction mention in model docs
* docs: tweak colqwen2 model doc
* docs: update reference checkpoint for ColPali to v1.3
* docs: simplify quickstart snippets
* docs: remove redundant `.eval()`
* refactor: use `can_return_tuple` decorator for ColPali and ColQwen2
* docs: fix copyright date
* docs: add missing copyright in tests
* fix: raise error when `initializer_range` is not in config
* docs: remove redundant `.eval()` in colpali doc
* fix: fix `get_text_config` now that Qwen2VL has a proper `text_config` attribute
See https://github.com/huggingface/transformers/pull/37268 for details about changes in Qwen2VL's config.
* fix: add missing `initializer_range` attribute in `ColQwen2Config`
* fix: use `get_text_config` in `resize_token_embeddings`
* update colwen2 with auto_docstring
* docs: fix wrong copyright year
* chore: remove `raise` as `initializer_range` has a default value in `ColQwen2Config`
* refactor: merge `inner_forward` into `forward`
* Refactor colqwen2 after refactoring of qwen2VL, use modular for modeling code
* protect torch import in modular to protect in processing
* protect torch import in modular to protect in processing
* tests: fix hf model path in ColQwen2 integration test
* docs: clarify `attn_implementation` and add comments
* docs: add fallback snippet for using offline PIL dummy images
* docs: temporarily revert attn_implementation to `None` while sdpa is not fixed
* docs: tweaks in colpali/colqwen2 quick start snippets
* fix: add missing flags to enable SDPA/Flex Attention in ColQwen2 model
* fix: add missing changes in modular file
* fix modeling tests
---------
Co-authored-by: yonigozlan <yoni.gozlan@huggingface.co>
* updates
* fixup
* fix tests
* fix test
* fix
* let it be here for now, till monday
* two more fixes
* persimmon
* fixup
* fix
* fixup
* make sure fuyu runs now that LM has new attn API
* fixup + tests
* qwen vl uses new mask interface as well
* qwen image features format
* update
* remove image_sizes
* address comments
* i am dumb...
* start refactoring whisper
* revert for now
* first step
* carry over attn fixes
* check if this works
* whisper has an off by one somewhere - cutting mask in any interface
* make it based on interface
* remove some tests that were skipped but now work
* some fixes for whisper tests
* interface changes
* change the order of fix
* some attention adjustments for eager + TP
* fix scaling
* mask changes
* why does whisper contain those extra seq lens?
* fix from config for fa2 as input_ids is invalid
* fix another test
* another fix
* disable flex attn due to compile issues
* copies and refactor for qwen audio since it somewhat relies on whisper
* fix scaling and smaller things
* retrigger
* new new interface version + more fixups
* adjust qwen
* add comment
* forgot this one
* change copies as whisper cuts on the mask
* add guard
* add flex attention
* switch to new mask function + add skips for torchscript
* remove old api with cache position
* last changes?
* trigger ci
* Firstly: Better detection of when we're a custom class
* Trigger tests
* Let's break everything
* make fixup
* fix mistaken line doubling
* Let's try to get rid of it from config classes at least
* Let's try to get rid of it from config classes at least
* Fixup image processor
* no more circular import
* Let's go back to setting `_auto_class` again
* Let's go back to setting `_auto_class` again
* stash commit
* Revert the irrelevant changes until we figure out AutoConfig
* Change tests since we're breaking expectations
* make fixup
* do the same for all custom classes
* Cleanup for feature extractor tests
* Cleanup tokenization tests too
* typo
* Fix tokenizer tests
* make fixup
* fix image processor test
* make fixup
* Remove warning from register_for_auto_class
* Stop adding model info to auto map entirely
* Remove todo
* Remove the other todo
* Let's start slapping _auto_class on models why not
* Let's start slapping _auto_class on models why not
* Make sure the tests know what's up
* Make sure the tests know what's up
* Completely remove add_model_info_to_*
* Start adding _auto_class to models
* Start adding _auto_class to models
* Add a flaky decorator
* Add a flaky decorator and import
* stash commit
* More message cleanup
* make fixup
* fix indent
* Fix trust_remote_code prompts
* make fixup
* correct indentation
* Reincorporate changes into dynamic_module_utils
* Update call to trust_remote_code
* make fixup
* Fix video processors too
* Fix video processors too
* Remove is_flaky additions
* make fixup
* 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>
* 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
* 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>
* 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>
* 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>
