* test
* up
* up
* Empty test commit
* up
* update tests
* up
* fix some vision models
* correct
* correct docs
* Trigger notification
* finalize
* check
* correct quicktour
* Apply suggestions from code review
* improve doctests
* Trigger Build
* next try
* next try
* and again
* Output current clone information
* Output current clone information
* Correct path
* add tf round again
* revert to daily job
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
* Seed get_train_sampler's generator with arg seed to improve reproducibility
and make the world_size<=1 code path more similar to the others
* move test file into trainer test explicitly
* dumb typo
* make style lint happy
* per discussion, switch to data_seed
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* added classes to get started with constrained beam search
* in progress, think i can directly force tokens now but not yet with the round robin
* think now i have total control, now need to code the bank selection
* technically works as desired, need to optimize and fix design choices leading to undersirable outputs
* complete PR #1 without disjunctive decoding
* removed incorrect tests
* Delete k.txt
* Delete test.py
* Delete test.sh
* revert changes to test scripts
* genutils
* full implementation with testing, no disjunctive yet
* shifted docs
* passing all tests realistically ran locally
* removing accidentally included print statements
* fixed source of error in initial PR test
* fixing the get_device() vs device trap
* fixed documentation docstrings about constrained_beam_search
* fixed tests having failing for Speech2TextModel's floating point inputs
* fix cuda long tensor
* added examples and testing for them and founx & fixed a bug in beam_search and constrained_beam_search
* deleted accidentally added test halting code with assert False
* code reformat
* Update tests/test_generation_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update tests/test_generation_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update tests/test_generation_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update tests/test_generation_utils.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update tests/test_generation_utils.py
* fixing based on comments on PR
* took out the testing code that should but work fails without the beam search moditification ; style changes
* fixing comments issues
* docstrings for ConstraintListState
* typo in PhrsalConstraint docstring
* docstrings improvements
* finished adding what is sort of an opinionated implementation of disjunctive generation, but it revealed errors in inner beam search logic during testing.
* fixed bug found in constrained beam search that used beam_idx that were not global across all the batches
* disjunctive constraint working 100% correctly
* passing all tests
* Accidentally included mlruns
* Update src/transformers/generation_beam_constraints.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/transformers/generation_beam_constraints.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* complete overhaul of type complexities and other nits
* strict type checks in generate()
* fixing second round of feedback by narsil
* fixed failing generation test because of type check overhaul
* generation test fail fix
* fixing test fails
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Do not change the output from tuple to list - to match PT's version
* Fix the same issues for 5 other models and the template
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Fix to support fast tokenizer with `CLIPProcessor`
* Update CLIPProcessor test for fast tokenizer
* Fix Docstring Style
* Rename into meaningful Variable name in test code
* send PyTorch inputs to the correct device
* Fix: TypeError: can't convert cuda:0 device type tensor to numpy. Use Tensor.cpu() to copy the tensor to host memory first.
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* Update delete-dev-doc job to match build-dev-doc
* More debug info
* More debug info
* Stash if needed
* Remove the comment update
* Fix paths
* Wtf is going on..
* Fix git status test
* Try another way
* I don't understand what's happening
* Bash shell
* What's happening now...
* What's happening now...
* Try like this
* Back to trying to use bash
* And like that?
* Refine tests
* Stash after adding new files
* Stash after adding new files
* Proper commit sha and PR number
* Address review comments
