* 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>
* first commit
* ResNet model correctly implemented.
basic modeling + weights conversion is done
removed unused doc
mdx file
doc and conversion script
added feature_extractor to auto
test
minor changes + style + quality
doc
test
Delete process.yml
A left over from my attempt of running circleci locally
* minor changes
* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* new test format
* minor changes from conversations
* minor changes from conversations
* make style + quality
* readded the tests
* test + README
* minor changes from conversations
* error in README
* make fix-copies
* removed regression for classification head
* make quality
* fixed loss control flow
* fixed loss control flow
* resolved conversations
* Apply suggestions from code review
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* READMEs
* index.mdx
* minor changes
* updated tests and models
* unused import
* outputs
* Update docs/source/model_doc/resnet.mdx
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* added embeddings_size
* Apply suggestions from code review
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* conversation
* added push to hub
* test
* embedding_size
* make fix-copies
* resolved conversations
* CI
* changed organization
* minor changes
* CI
* minor changes
* conversations
* conversation
* doc
* tests
* removed unused docstring
* conversation
* removed unused outputs
* CI
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
* Make TF pt-tf equivalence test more aggressive
* Fix for TFConvNextModelTest and TFTransfoXLModelTest
* fix kwargs for outputs
* clean-up
* Add docstring for check_outputs()
* remove: need to rename encoder-decoder
* clean-up
* send PyTorch things to the correct device
* Add back the accidentally removed test case in test_pt_tf_model_equivalence()
* Fix: change to tuple before calling check_outputs()
* Fix: tfo could be a list
* use to_tuple()
* allow tfo only to be tuple or tensor
* allow tfo to be list or tuple for now + style change
* minor fix
* remove np.copy and update comments
* tfo -> tf_output, same for pt
* Add more detailed comment
* remove the incorrect comment
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
* add possibility to softly regulate length when using sampling method in model.generate() function
* fix test config, fix formatting
* fix rag integration, fix docstyling
* fix wrong docstring
* change param to tuple, add test
* fix old param in rag_model, remove unused import
* change test according to new param
* fix formatting
* fix test case
* fix doc style
* move start_length calculation to Logitprocessor
* add possibility to softly regulate length when using sampling method in model.generate() function
* fix rag integration, fix docstyling
* fix test config, fix formatting
* change param to tuple, add test
* fix old param in rag_model, remove unused import
* add possibility to softly regulate length when using sampling method in model.generate() function
* change param to tuple, add test
* fix old param in rag_model, remove unused import
* remove unused import
* fix small errors
* fix test
* add possibility to softly regulate length when using sampling method in model.generate() function
* fix test config, fix formatting
* fix rag integration, fix docstyling
* change param to tuple, add test
* fix old param in rag_model, remove unused import
* change test according to new param
* fix test case
* move start_length calculation to Logitprocessor
* add possibility to softly regulate length when using sampling method in model.generate() function
* fix rag integration, fix docstyling
* fix test config, fix formatting
* change param to tuple, add test
* fix old param in rag_model, remove unused import
* add possibility to softly regulate length when using sampling method in model.generate() function
* fix test config, fix formatting
* fix rag integration, fix docstyling
* add possibility to softly regulate length when using sampling method in model.generate() function
* fix rag integration, fix docstyling
* change param to tuple, add test
* fix old param in rag_model, remove unused import
* fix small errors
* Update src/transformers/generation_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* Update src/transformers/generation_utils.py
* Update src/transformers/generation_utils.py
* fix docstring, add type ind model rag
* fix docstrings
* introduce seq_length variable for cleaner code
* fix black formatting
* add input_ids_seq_length to modeling_rag
* add input_ids_seq_length to test
* retrigger checks
* retrigger checks
Co-authored-by: Kevin Bondzio <kev@AIM-LAP-02.local>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Kevin Bondzio <kev@AIM-LAP-02.fritz.box>
* Fix duplicate arguments passed to dummy inputs in ONNX export
* Fix M2M100 ONNX config
* Ensure we check PreTrained model only if torch is available
* Remove TensorFlow tests for models without PyTorch parity
* Add ONNX support for ViT
* Refactor to use generic preprocessor
* Add vision dep to tests
* Extend ONNX slow tests to ViT
* Add dummy image generator
* Use model_type to determine modality
* Add deprecation warnings for tokenizer argument
* Add warning when overwriting the preprocessor
* Add optional args to docstrings
* Add minimum PyTorch version to OnnxConfig
* Refactor OnnxConfig class variables from CONSTANT_NAME to snake_case
* Add reasonable value for default atol
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
* 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>
* 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>
* 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>
