* Adding new train_step logic to make things less confusing for users
* DO NOT ASK WHY WE NEED THAT SUBCLASS
* Metrics now working, at least for single-output models with type annotations!
* Updates and TODOs for the new train_step
* Make fixup
* Temporary test workaround until T5 has types
* Temporary test workaround until T5 has types
* I think this actually works! Needs a lot of tests though
* MAke style/quality
* Revert changes to T5 tests
* Deleting the aforementioned unmentionable subclass
* Deleting the aforementioned unmentionable subclass
* Adding a Keras API test
* Style fixes
* Removing unneeded TODO and comments
* Update test_step too
* Stop trying to compute metrics with the dummy_loss, patch up test
* Make style
* make fixup
* Docstring cleanup
* make fixup
* make fixup
* Stop expanding 1D input tensors when using dummy loss
* Adjust T5 test given the new compile()
* make fixup
* Skipping test for convnext
* Removing old T5-specific Keras test now that we have a common one
* make fixup
* make fixup
* Only skip convnext test on CPU
* Update src/transformers/modeling_tf_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/modeling_tf_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Avoiding TF import issues
* make fixup
* Update compile() to support TF 2.3
* Skipping model.fit() on template classes for now
* Skipping model.fit() on template class tests for now
* Replace ad-hoc solution with find_labels
* make fixup
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Split file_utils in several submodules
* Fixes
* Add back more objects
* More fixes
* Who exactly decided to import that from there?
* Second suggestion to code with code review
* Revert wront move
* Fix imports
* Adapt all imports
* Adapt all imports everywhere
* Revert this import, will fix in a separate commit
* First attempt at TF XLA generation
* Fix comments
* Update XLA greedy generate with direct XLA calls
* Support attention mask, prepare_inputs_for_generation no longer hardcoded for greedy
* Handle position_ids correctly
* make xla generate work for non xla case
* force using xla generate
* refactor
* more fixes
* finish cleaning
* finish
* finish
* clean gpt2 tests
* add gpt2 tests
* correct more cases
* up
* finish
* finish
* more fixes
* flake 8 stuff
* final rag fix
* Update src/transformers/models/rag/modeling_tf_rag.py
* finish t5 as well
* finish
* Update src/transformers/generation_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Add TF logits wrappers
* Add sample method
* add tests for TF logit wrappers
* TF generate sample tests now run on CPU
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>
