* A fun new PR where I break the entire codebase again
* A fun new PR where I break the entire codebase again
* Handle cross-attention
* Move calls to model(model.dummy_inputs) to the new build() method
* Seeing what fails with the build context thing
* make fix-copies
* Let's see what fails with new build methods
* Fix the pytorch crossload build calls
* Fix the overridden build methods in vision_text_dual_encoder
* Make sure all our build methods set self.built or call super().build(), which also sets it
* make fix-copies
* Remove finished TODO
* Tentatively remove unneeded (?) line
* Transpose b in deberta correctly and remove unused threading local
* Get rid of build_with_dummies and all it stands for
* Rollback some changes to TF-PT crossloading
* Correctly call super().build()
* 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
* First commit for the improved PT-TF weight loading
* Remove workarounds from TFEncoderDecoder tests
* Allow a custom weight renaming function in from_pretrained and use that to clean up EncoderDecoder
* make fixup
* First attempt at visionencoderdecoder
* Disable tensorfloat32 in tests to get consistent outputs
* Quick fix to tf_vision_encoder_decoder tests
* make fixup
* Update Blenderbot tests
* Remove unused arg in modeling_tf_opt
* load_tf_sharded_weights had strict=True! This meant transfer learning was impossible, so I'm setting it to False.
* Support prefixes when loading sharded TF checkpoints
* make fixup
* Add test to load sharded models with a weight prefix
* Fix sharded weight loading test
* Add a test for transfer from a sharded checkpoint
* make fixup
* Add test to check that crossloading from PT with a prefix works
* Refactor from_pretrained in the encoderdecoder classes
* Refactor from_pretrained in the encoderdecoder classes
* missmatched -> mismatched
* Explicitly check for None
* No comments showing my very impressive and attractive knowledge of Py3.9+
* Disable TF32 across all TF 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
* 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
* First step of PT->TF for composite models
* Update the tests
* For VisionEncoderDecoderModel
* Fix
* Fix
* Add comment
* Fix
* clean up import
* Save memory
* For (TF)EncoderDecoderModel
* For (TF)EncoderDecoderModel
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
