Files
HuggingFace_transformer/docs/source
StevenBucaille a88ea9cbc8 Add EfficientLoFTR model (#36355)
* initial commit

* Apply suggestions from code review

Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>

* fix: various typos, typehints, refactors from suggestions

* fix: fine_matching method

* Added EfficientLoFTRModel and AutoModelForKeypointMatching class

* fix: got rid of compilation breaking instructions

* docs: added todo for plot

* fix: used correct hub repo

* docs: added comments

* fix: run modular

* doc: added PyTorch badge

* fix: model repo typo in config

* fix: make modular

* fix: removed mask values from outputs

* feat: added plot_keypoint_matching to EfficientLoFTRImageProcessor

* feat: added SuperGlueForKeypointMatching to AutoModelForKeypointMatching list

* fix: reformat

* refactor: renamed aggregation_sizes config parameter into q, kv aggregation kernel size and stride

* doc: added q, kv aggregation kernel size and stride doc to config

* refactor: converted efficientloftr implementation from modular to copied from mechanism

* tests: overwrote batching_equivalence for "keypoints" specific tests

* fix: changed EfficientLoFTRConfig import in test_modeling_rope_utils

* fix: make fix-copies

* fix: make style

* fix: update rope function to make meta tests pass

* fix: rename plot_keypoint_matching to visualize_output for clarity

* refactor: optimize image pair processing by removing redundant target size calculations

* feat: add EfficientLoFTRImageProcessor to image processor mapping

* refactor: removed logger and updated attention forward

* refactor: added auto_docstring and can_return_tuple decorators

* refactor: update type imports

* refactor: update type hints from List/Dict to list/dict for consistency

* refactor: update MODEL_MAPPING_NAMES and __all__ to include LightGlue and AutoModelForKeypointMatching

* fix: change type hint for size parameter in EfficientLoFTRImageProcessor to Optional[dict]

* fix typing

* fix some typing issues

* nit

* a few more typehint fixes

* Remove output_attentions and output_hidden_states from modeling code

* else -> elif to support efficientloftr

* nit

* tests: added EfficientLoFTR image processor tests

* refactor: reorder functions

* chore: update copyright year in EfficientLoFTR test file

* Use default rope

* Add docs

* Update visualization method

* fix doc order

* remove 2d rope test

* Update src/transformers/models/efficientloftr/modeling_efficientloftr.py

* fix docs

* Update src/transformers/models/efficientloftr/image_processing_efficientloftr.py

* update gradient

* refactor: removed unused codepath

* Add motivation to keep postprocessing in modeling code

* refactor: removed unnecessary variable declarations

* docs: use load_image from image_utils

* refactor: moved stage in and out channels computation to configuration

* refactor: set an intermediate_size parameter to be more explicit

* refactor: removed all mentions of attention masks as they are not used

* refactor: moved position_embeddings to be computed once in the model instead of every layer

* refactor: removed unnecessary hidden expansion parameter from config

* refactor: removed completely hidden expansions

* refactor: removed position embeddings slice function

* tests: fixed broken tests because of previous commit

* fix is_grayscale typehint

* not refactoring

* not renaming

* move h/w to embeddings class

* Precompute embeddings in init

* fix: replaced cuda device in convert script to accelerate device

* fix: replaced stevenbucaille repo to zju-community

* Remove accelerator.device from conversion script

* refactor: moved parameter computation in configuration instead of figuring it out when instantiating a Module

* fix: removed unused attributes in configuration

* fix: missing self

* fix: refactoring and tests

* fix: make style

---------

Co-authored-by: steven <steven.bucaille@buawei.com>
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
2025-07-22 10:53:16 +01:00
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