GitLab

* Draft pipeline

* Fixup

* Fix docstrings

* Update doctest

* Update pipeline_model_mapping

* Update docstring

* Update tests

* Update src/transformers/pipelines/image_feature_extraction.py
Co-authored-by: Omar Sanseviero <osanseviero@gmail.com>

* Fix docstrings - review comments

* Remove pipeline mapping for composite vision models

* Add to pipeline tests

* Remove for flava (multimodal)

* safe pil import

* Add requirements for pipeline run

* Account for super slow efficientnet

* Review comments

* Fix tests

* Swap order of kwargs

* Use build_pipeline_init_args

* Add back FE pipeline for Vilt

* Include image_processor_kwargs in docstring

* Mark test as flaky

* Update TODO

* Update tests/pipelines/test_pipelines_image_feature_extraction.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Add license header

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Co-authored-by: Omar Sanseviero <osanseviero@gmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update forward signature

* Empty-Commit

* Add type annotations to TFConvNextDropPath

* Use tf.debugging.assert_equal for TFConvNextEmbeddings shape check

* Add TensorFlow implementation of ConvNeXTV2

* check_docstrings: add TFConvNextV2Model to exclusions

TFConvNextV2Model and TFConvNextV2ForImageClassification have docstrings
which are equivalent to their PyTorch cousins, but a parsing issue prevents them
from passing the test.

Adding exclusions for these two classes as discussed in #25558.

fix
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Add TFBlipForConditionalGeneration

* update pipeline_model_mapping

* Add import

* Revert changes in GPTSanJapaneseTest

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Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Add out_indices to backbones, deprecate out_features

* Update - can specify both out_features and out_indices but not both

* Add backbone mixin tests

* Test tidy up

* Add test_backbone for convnext

* Remove redefinition of method

* Update for Dinat and Nat backbones

* Update tests

* Smarter indexing

* Add checks on config creation for backbone

* PR comments

* Add ConvNeXt V2 to transformers
* TF model is separated from the PR to fix issues