* add more cases
* fix method not found in unittest
Signed-off-by: Lin, Fanli <fanli.lin@intel.com>
* fix more cases
* add more models
* add all
* no unittest.case
* remove for oneformer
* fix style
---------
Signed-off-by: Lin, Fanli <fanli.lin@intel.com>
* save/load sub-configs
* nit forgot these
* fix copies
* move test to common
* use dict for sub-configs
* add load-save-laod test
* clean up modeling check
* oops this are correct keys
* fix some tests, missed some composite configs
* this model was missed
* first try
* codestyle
* idefics2 is happy
* [run-slow] llava, llava_next, video_llava, vipllava, llava_next_video, idefics, idefics2, kosmos2, fuyu, blip, blip_2, instructblip, instructblipvideo, paligemma
* fix-copies
* [run-slow] llava, llava_next, video_llava, vipllava, llava_next_video, idefics, idefics2, kosmos2, fuyu, blip, blip_2, instructblip, instructblipvideo
* blip-2 needs to init vision from config
* when was this removed O_o
* minor fix
* tests
* this way?
* tests
* model-agnostic code
* codestyle
* add tests for idefics
* modify general test for VLMs
* no generation test for vlm yet!
* no generation test here also
* wanr in VIT-SDPA if output attn
* add more tests
* user can pass dict as attn impl
* repo consistency
* update
* muicgen
* no prints
* forgot speech enc-dec and clip
* how many composite models we have?
* musicgen meelody is same as mudicgen
* +siglip
* fix tests + add some more
* remove idefics custom overriden code
* make idefics2 automappable
* nits
* skip tests
* doctests
* Update src/transformers/models/idefics2/configuration_idefics2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/clip/test_modeling_clip.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/idefics2/test_modeling_idefics2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update tests/models/idefics2/test_modeling_idefics2.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Update src/transformers/configuration_utils.py
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* major update, no need for automap
* clean up
* add FA2 test
* more tests
* style
* skip tests
* why did these started failing now?
* no attributes for FA2 needed
* one tiny test
* address comment about FA2 false warning
* style
* add new models and resolve conflicts
* fix copies
* let it be this way for now, come back tomorrow to review
* some more fixes
* update
* more updates
* update
* fix copies
* style and tests
* another big update
* fix tests
* fix tests
* update
* another update
* fix tests
* fix copies
* fix tests
---------
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
This commit fixes the following errors:
* Fix "expected all tensors to be on the same device" error
* Fix "can't convert device type tensor to numpy"
According to pytorch documentation torch.Tensor.numpy(force=False)
performs conversion only if tensor is on CPU (plus few other restrictions)
which is not the case. For our case we need force=True since we just
need a data and don't care about tensors coherency.
Fixes: #33517
See: https://pytorch.org/docs/2.4/generated/torch.Tensor.numpy.html
Signed-off-by: Dmitry Rogozhkin <dmitry.v.rogozhkin@intel.com>
* Draft fast image processors
* Draft working fast version
* py3.8 compatible cache
* Enable loading fast image processors through auto
* Tidy up; rescale behaviour based on input type
* Enable tests for fast image processors
* Smarter rescaling
* Don't default to Fast
* Safer imports
* Add necessary Pillow requirement
* Woops
* Add AutoImageProcessor test
* Fix up
* Fix test for imagegpt
* Fix test
* Review comments
* Add warning for TF and JAX input types
* Rearrange
* Return transforms
* NumpyToTensor transformation
* Rebase - include changes from upstream in ImageProcessingMixin
* Safe typing
* Fix up
* convert mean/std to tesnor to rescale
* Don't store transforms in state
* Fix up
* Update src/transformers/image_processing_utils_fast.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/auto/image_processing_auto.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/auto/image_processing_auto.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Update src/transformers/models/auto/image_processing_auto.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
* Warn if fast image processor available
* Update src/transformers/models/vit/image_processing_vit_fast.py
* Transpose incoming numpy images to be in CHW format
* Update mapping names based on packages, auto set fast to None
* Fix up
* Fix
* Add AutoImageProcessor.from_pretrained(checkpoint, use_fast=True) test
* Update src/transformers/models/vit/image_processing_vit_fast.py
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* Add equivalence and speed tests
* Fix up
---------
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>
Co-authored-by: Pavel Iakubovskii <qubvel@gmail.com>
* 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
* 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>
* Port core files + ESM (because ESM code is odd)
* Search-replace in modelling code
* Fix up transfo_xl as well
* Fix other core files + tests (still need to add correct import to tests)
* Fix cookiecutter
* make fixup, fix imports in some more core files
* Auto-add imports to tests
* Cleanup, add imports to sagemaker tests
* Use correct exception for importing tf_keras
* Fixes in modeling_tf_utils
* make fixup
* Correct version parsing code
* Ensure the pipeline tests correctly revert to float32 after each test
* Ensure the pipeline tests correctly revert to float32 after each test
* More tf.keras -> keras
* Add dtype cast
* Better imports of tf_keras
* Add a cast for tf.assign, just in case
* Fix callback imports
* try to stylify using ruff
* might need to remove these changes?
* use ruf format andruff check
* use isinstance instead of type comparision
* use # fmt: skip
* use # fmt: skip
* nits
* soem styling changes
* update ci job
* nits isinstance
* more files update
* nits
* more nits
* small nits
* check and format
* revert wrong changes
* actually use formatter instead of checker
* nits
* well docbuilder is overwriting this commit
* revert notebook changes
* try to nuke docbuilder
* style
* fix feature exrtaction test
* remve `indent-width = 4`
* fixup
* more nits
* update the ruff version that we use
* style
* nuke docbuilder styling
* leve the print for detected changes
* nits
* Remove file I/O
Co-authored-by: charliermarsh
<charlie.r.marsh@gmail.com>
* style
* nits
* revert notebook changes
* Add # fmt skip when possible
* Add # fmt skip when possible
* Fix
* More ` # fmt: skip` usage
* More ` # fmt: skip` usage
* More ` # fmt: skip` usage
* NIts
* more fixes
* fix tapas
* Another way to skip
* Recommended way
* Fix two more fiels
* Remove asynch
Remove asynch
---------
Co-authored-by: charliermarsh <charlie.r.marsh@gmail.com>
* stronger GC tests
* better tests and skip failing tests
* break down into 3 sub-tests
* break down into 3 sub-tests
* refactor a bit
* more refactor
* fix
* last nit
* credits contrib and suggestions
* credits contrib and suggestions
---------
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
Co-authored-by: amyeroberts <22614925+amyeroberts@users.noreply.github.com>
* Add FlaxClipTextModelWithProjection
This is necessary to support the Flax port of Stable Diffusion XL: fb6d705fb5/text_encoder_2/config.json (L3)
Co-authored-by: Martin Müller <martin.muller.me@gmail.com>
Co-authored-by: Juan Acevedo <juancevedo@gmail.com>
* Use FlaxCLIPTextModelOutput
* make fix-copies again
* Apply suggestions from code review
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
* Use `return_dict` for consistency with other uses.
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
* Fix docstring example.
* Add new model to FlaxCLIPTextModelTest
* Add to IGNORE_NON_AUTO_CONFIGURED list
* Fix naming convention.
---------
Co-authored-by: Martin Müller <martin.muller.me@gmail.com>
Co-authored-by: Juan Acevedo <juancevedo@gmail.com>
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
* Refactor image processor test mixin
- Move test_call_numpy, test_call_pytorch, test_call_pil to mixin
- Rename mixin to reflect handling of logic more than saving
- Add prepare_image_inputs, expected_image_outputs for tests
* Fix for oneformer
* fix: Apostraphe splitting in the BasicTokenizer for CLIPTokenizer
* account for apostrophe at start of new word
* remove _run_split_on_punc, use re.findall instead
* remove debugging, make style and quality
* use pattern and punc splitting, repo-consistency will fail
* remove commented out debugging
* adds bool args to BasicTokenizer, remove pattern
* do_split_on_punc default True
* clean stray comments and line breaks
* rebase, repo-consistency
* update to just do punctuation split
* add unicode normalizing back
* remove redundant line
* hidden layers, huh, what are they good for (absolutely nothing)
* Some tests break with 1 hidden layer, use 2
* Use 1 hidden layer in a few slow models
* Use num_hidden_layers=2 everywhere
* Slightly higher tol for groupvit
* Slightly higher tol for groupvit
* Rework TF type hints to use | None instead of Optional[] for tf.Tensor
* Rework TF type hints to use | None instead of Optional[] for tf.Tensor
* Don't forget the imports
* Add the imports to tests too
* make fixup
* Refactor tests that depended on get_type_hints
* Better test refactor
* Fix an old hidden bug in the test_keras_fit input creation code
* Fix for the Deit tests
* Result of black 23.1
* Update target to Python 3.7
* Switch flake8 to ruff
* Configure isort
* Configure isort
* Apply isort with line limit
* Put the right black version
* adapt black in check copies
* Fix copies
* Update imports and test fetcher
* Revert but keep test fetcher update
* Fix imports
* Fix all imports
* Replace fe with ip names
* Add generate kwargs to `AutomaticSpeechRecognitionPipeline` (#20952)
* Add generate kwargs to AutomaticSpeechRecognitionPipeline
* Add test for generation kwargs
* Update image processor parameters if creating with kwargs (#20866)
* Update parameters if creating with kwargs
* Shallow copy to prevent mutating input
* Pass all args in constructor dict - warnings in init
* Fix typo
* Rename tester class
* Rebase and tidy up
* Fixup
* Use ImageProcessingSavingTestMixin
* Update property ref in tests
* Update property ref in tests
* Update recently merged in models
* Small fix
Co-authored-by: bofeng huang <bofenghuang7@gmail.com>
* allow loading projection in text and vision model
* begin tests
* finish test for CLIPTextModelTest
* style
* add slow tests
* add new classes for projection heads
* remove with_projection
* add in init
* add in doc
* fix tests
* fix some more tests
* fix copies
* fix docs
* remove leftover from fix-copies
* add the head models in IGNORE_NON_AUTO_CONFIGURED
* fix docstr
* fix tests
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* add docstr for models
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Add serving_output and serving methods to some vision models
* Add serving outputs for DeiT
* Don't convert hidden states - differing shapes
* Make saveable
* Fix up
* Make swin saveable
* Add in tests
* Fix funnel tests (can't convert to tensor)
* Fix numpy call
* Tidy up a bit
* Add in hidden states - resnet
* Remove numpy
* Fix failing tests - tensor shape and skipping tests
* Remove duplicated function
* PR comments - formatting and var names
* PR comments
Add suggestions made by Joao Gante:
* Use tf.shape instead of shape_list
* Use @tooslow decorator on tests
* Simplify some of the logic
* PR comments
Address Yih-Dar Sheih comments - making tensor names consistent and make types float
* Types consistent with docs; disable test on swin (slow)
* CI trigger
* Change input_features to float32
* Add serving_output for segformer
* Fixup
Co-authored-by: Amy Roberts <amyeroberts@users.noreply.github.com>
* Support for Bart and LayoutLM, and partial support for XLNet
* Support for mbart
* A lot of new models supported
* Support for other models
* LayoutLM fix
* Use strings instead of classes
* CLIP Serving
* Add type hints per code review
* Use black, flake8, and isort
* Update src/transformers/models/clip/modeling_tf_clip.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
* Rollback serving_output and add TODO
* Remove irrelevant portions of failing tests
* Revert "Rollback serving_output and add TODO"
This reverts commit a4abfa6ba3b7875a13538dbc2ddc4eb17dfcca8d.
* Rollback to original test/serving_output
* Fix unused var
* Apply suggestions from code review
* Update formatting with black
* Fix style again from rebase
* Update tests/models/clip/test_modeling_tf_clip.py
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: Sean Moriarity <sean.l.moriarity.mil@army.mil>
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
