* chore: fix typos in the tests
* chore: fix typos in the tests
* chore: fix typos in the tests
* chore: fix typos in the tests
* chore: fix typos in the tests
* chore: fix typos in the tests
* chore: fix typos in the tests
* chore: fix typos in the tests
* chore: fix typos in the tests
* chore: fix typos in the tests
* chore: fix typos in the tests
* chore: fix typos in the tests
* chore: fix typos in the tests
* fix: format codes
* chore: fix copy mismatch issue
* fix: format codes
* chore: fix copy mismatch issue
* chore: fix copy mismatch issue
* chore: fix copy mismatch issue
* chore: restore previous words
* chore: revert unexpected changes
* Add is_torch_greater_or_equal test decorator
* Add common test for torch.export
* Fix bit
* Fix focalnet
* Fix imagegpt
* Fix seggpt
* Fix swin2sr
* Enable torch.export test for vision models
* Enable test for video models
* Remove json
* Enable for hiera
* Enable for ijepa
* Fix detr
* Fic conditional_detr
* Fix maskformer
* Enable test maskformer
* Fix test for deformable detr
* Fix custom kernels for export in rt-detr and deformable-detr
* Enable test for all DPT
* Remove custom test for deformable detr
* Simplify test to use only kwargs for export
* Add comment
* Move compile_compatible_method_lru_cache to utils
* Fix beit export
* Fix deformable detr
* Fix copies data2vec<->beit
* Fix typos, update test to work with dict
* Add seed to the test
* Enable test for vit_mae
* Fix beit tests
* [run-slow] beit, bit, conditional_detr, data2vec, deformable_detr, detr, focalnet, imagegpt, maskformer, rt_detr, seggpt, swin2sr
* Add vitpose test
* Add textnet test
* Add dinov2 with registers
* Update tests/test_modeling_common.py
* Switch to torch.testing.assert_close
* Fix masformer
* Remove save-load from test
* Add dab_detr
* Add depth_pro
* Fix and test RT-DETRv2
* Fix dab_detr
* use torch.testing.assertclose instead to get more details about error in cis
* fix
* style
* test_all
* revert for I bert
* fixes and updates
* more image processing fixes
* more image processors
* fix mamba and co
* style
* less strick
* ok I won't be strict
* skip and be done
* up
* Rename to test_model_common_attributes
The method name is misleading - it is testing being able to get and set embeddings, not common attributes to all models
* Explicitly skip
* move scaling to nn.Module
* let the test be here for now (need to fix)
* failing tests
* last failing models
* Revert commit 4c14817f38
* clean-up
* oops forgot
* codestyle
* raise NotImplemented when possible
* Update tests/test_modeling_common.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* skip tests in respective modeling files
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Enable instantiating model with pretrained backbone weights
* Clarify pretrained import
* Use load_backbone instead
* Add backbone_kwargs to config
* Fix up
* Add tests
* Tidy up
* Enable instantiating model with pretrained backbone weights
* Update tests so backbone checkpoint isn't passed in
* Clarify pretrained import
* Update configs - docs and validation check
* Update src/transformers/utils/backbone_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Clarify exception message
* Update config init in tests
* Add test for when use_timm_backbone=True
* Use load_backbone instead
* Add use_timm_backbone to the model configs
* Add backbone_kwargs to config
* Pass kwargs to constructors
* Draft
* Fix tests
* Add back timm - weight naming
* More tidying up
* Whoops
* Tidy up
* Handle when kwargs are none
* Update tests
* Revert test changes
* Deformable detr test - don't use default
* Don't mutate; correct model attributes
* Add some clarifying comments
* nit - grammar is hard
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* add tests for batching support
* Update src/transformers/models/fastspeech2_conformer/modeling_fastspeech2_conformer.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* Update src/transformers/models/fastspeech2_conformer/modeling_fastspeech2_conformer.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* Update tests/test_modeling_common.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* Update tests/test_modeling_common.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* Update tests/test_modeling_common.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* fixes and comments
* use cosine distance for conv models
* skip mra model testing
* Update tests/models/vilt/test_modeling_vilt.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* finzalize and make style
* check model type by input names
* Update tests/models/vilt/test_modeling_vilt.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* fixed batch size for all testers
* Revert "fixed batch size for all testers"
This reverts commit 525f3a0a05.
* add batch_size for all testers
* dict from model output
* do not skip layoutlm
* bring back some code from git revert
* Update tests/test_modeling_common.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/test_modeling_common.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* clean-up
* where did minus go in tolerance
* make whisper happy
* deal with consequences of losing minus
* deal with consequences of losing minus
* maskformer needs its own test for happiness
* fix more models
* tag flaky CV models from Amy's approval
* make codestyle
---------
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Enable instantiating model with pretrained backbone weights
* Remove doc updates until changes made in modeling code
* Use load_backbone instead
* Add use_timm_backbone to the model configs
* Add missing imports and arguments
* Update docstrings
* Make sure test is properly configured
* Include recent DPT updates
* Enable instantiating model with pretrained backbone weights
* Update tests so backbone checkpoint isn't passed in
* Remove doc updates until changes made in modeling code
* Clarify pretrained import
* Update configs - docs and validation check
* Update src/transformers/utils/backbone_utils.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Clarify exception message
* Update config init in tests
* Add test for when use_timm_backbone=True
* Small test updates
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* [DETA] fix freeze/unfreeze function
* Update src/transformers/models/deta/modeling_deta.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/deta/modeling_deta.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* add freeze/unfreeze test case in DETA
* fix type
* fix typo 2
* fix : enable aux and enc loss in training pipeline
* Add unsynced variables from original DETA for training
* modification for passing CI test
* make style
* make fix
* manual make fix
* change deta_modeling_test of configuration 'two_stage' default to TRUE and minor change of dist checking
* remove print
* divide configuration in DetaModel and DetaForObjectDetection
* image smaller size than 224 will give topk error
* pred_boxes and logits should be equivalent to two_stage_num_proposals
* add missing part in DetaConfig
* Update src/transformers/models/deta/modeling_deta.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* add docstring in configure and prettify TO DO part
* change distribute related code to accelerate
* Update src/transformers/models/deta/configuration_deta.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/deta/test_modeling_deta.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* protect importing accelerate
* change variable name to specific value
* wrong import
* fix aux_loss in conditional_detr
* add test aux_loss
* add aux_loss test in deta and table_transformer
* fix yolos since it doesn't have auxiliary function
* fix maskformer auxiliary_loss related code
* make style
* change param 'auxiliary_loss' to 'use_auxiliary_loss'
* change param 'auxiliary_loss' to 'use_auxiliary_loss' in tests
* make style & fix-copies, also revert yolos related parameter
* revert variable name 'use_auxiliary_loss' to 'auxiliary_loss' due to DetrConfig
* revert variable name in yolos
* revert maskformer
* add aux_loss test in maskformer
* make style
* Update src/transformers/models/yolos/configuration_yolos.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* move generation_*.py src files into generation/*.py
* populate generation.__init__ with lazy loading
* move imports and references from generation.xxx.object to generation.object
