GitLab

TF: XLA beam search + most generation-compatible models are now also XLA-generate-compatible (#17857)

* working beam search 🎉

* XLA generation compatible with ALL classes

* add xla generation slow test

* Also propagate changes to blenderbot, blenderbot_small, marian, mbart, and pegasus

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

* Black preview

* Fixup too!

* Fix check copies

* Use the same version as the CI

* Bump black

* move test model folders (TODO: fix imports and others)

* fix (potentially partially) imports (in model test modules)

* fix (potentially partially) imports (in tokenization test modules)

* fix (potentially partially) imports (in feature extraction test modules)

* fix import utils.test_modeling_tf_core

* fix path ../fixtures/

* fix imports about generation.test_generation_flax_utils

* fix more imports

* fix fixture path

* fix get_test_dir

* update module_to_test_file

* fix get_tests_dir from wrong transformers.utils

* update config.yml (CircleCI)

* fix style

* remove missing imports

* update new model script

* update check_repo

* update SPECIAL_MODULE_TO_TEST_MAP

* fix style

* add __init__

* update self-scheduled

* fix add_new_model scripts

* check one way to get location back

* python setup.py build install

* fix import in test auto

* update self-scheduled.yml

* update slack notification script

* Add comments about artifact names

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

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* 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>

* Add unpack_inputs to remaining models

* removed kwargs to `call()` in TF models

* fix TF T5 tests

* use random_attention_mask for TF tests

* Fix for TFCLIP test (for now).
Co-authored-by: ydshieh <ydshieh@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>

* Remove packed past from generation_tf_utils

* update models with the new past format

* update template accordingly

* 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>

* Add GPT2 TF generate sample test with all logits processor

* Add T5 generate sample test

* Per-folder tests reorganization
Co-authored-by: sgugger <sylvain.gugger@gmail.com>
Co-authored-by: Stas Bekman <stas@stason.org>

* TF generate start refactor

* Add tf tests for sample generate

* re-organize

* boom boom

* Apply suggestions from code review

* re-add

* add all code

* make random greedy pass

* make encoder-decoder random work

* further improvements

* delete bogus file

* make gpt2 and t5 tests work

* finish logits tests

* correct logits processors

* correct past / encoder_outputs drama

* refactor some methods

* another fix

* refactor shape_list

* fix more shape list

* import shape
_list

* finish docs

* fix imports

* make style

* correct tf utils

* Fix TFRag as well

* Apply Lysandre's and Sylvais suggestions

* Update tests/test_generation_tf_logits_process.py
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* Update src/transformers/tf_utils.py
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* remove cpu according to gante

* correct logit processor
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* Fix TF MT5 vocab resize

* more assertive testing

* TF Model train and eval step metrics for seq2seq models.

When using a model with a seq2seq output compute metrics against logits.

* Removing vestigial code
Co-authored-by: matt <rocketknight1@gmail.com>

* allow tf to use uneven num of layers

* add tokenizer

* finish docs

* finish docs

* Apply suggestions from code review

* include in index

* finish

* Update docs/source/model_doc/byt5.rst
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* apply sylvais suggestions

* make style
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Fix Bart

* Fix Blenderbot{,_small}

* Fix LED

* Fix Marian

* Fix MBart

* Fix Pegasus

* Fix T5

* Add test for generation with head_mask

* Add a common TF test

* Override a test for the LED model as head masking is not yet properly implemented

* Remove all head_masks from input preparation for LED

* Drop masking for T5 as it needs a bit of refactor

* rework savedmodel slow test

* Improve savedmodel tests

* Remove useless content

* Fix head_mask and decoder_head_mask in TFT5 models

* Enable test_headmasking both fot TFT5 tester
and TFT5EncoderOnly tester
Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com>

* Add check-ops script

* Finish to implement check_tf_ops and start the test

* Make the test mandatory only for BERT

* Update tf_ops folder

* Remove useless classes

* Add the ONNX test for GPT2 and BART

* Add a onnxruntime slow test + better opset flexibility

* Fix test + apply style

* fix tests

* Switch min opset from 12 to 10

* Update src/transformers/file_utils.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Fix GPT2

* Remove extra shape_list usage

* Fix GPT2

* Address Morgan's comments
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Add head_mask/decoder_head_mask for TF BART models

* Add head_mask and decoder_head_mask input arguments for TF BART-based
models as a TF counterpart to the PR #9569

* Add test_headmasking functionality to tests/test_modeling_tf_common.py

* TODO: Add a test to verify that we can get a gradient back for
importance score computation

* Remove redundant #TODO note

Remove redundant #TODO note from tests/test_modeling_tf_common.py

* Fix assertions

* Make style

* Fix ...Model input args and adjust one new test

* Add back head_mask and decoder_head_mask to BART-based ...Model
after the last commit

* Remove head_mask ande decoder_head_mask from input_dict
in TF test_train_pipeline_custom_model as these two have different
shape than other input args (Necessary for passing this test)

* Revert adding global_rng in test_modeling_tf_common.py

* Start rework resizing

* Rework bias/decoder resizing

* Full resizing rework

* Full resizing rework

* Start to update the models with the new approach

* Finish to update the models

* Update all the tests

* Update the template

* Fix tests

* Fix tests

* Test a new approach

* Refactoring

* Refactoring

* Refactoring

* New rework

* Rework BART

* Rework bert+blenderbot

* Rework CTRL

* Rework Distilbert

* Rework DPR

* Rework Electra

* Rework Flaubert

* Rework Funnel

* Rework GPT2

* Rework Longformer

* Rework Lxmert

* Rework marian+mbart

* Rework mobilebert

* Rework mpnet

* Rework openai

* Rework pegasus

* Rework Roberta

* Rework T5

* Rework xlm+xlnet

* Rework template

* Fix TFT5EncoderOnly + DPRs

* Restore previous methods

* Fix Funnel

* Fix CTRL and TransforXL

* Apply style

* Apply Sylvain's comments

* Restore a test in DPR

* Address the comments

* Fix bug

* Apply style

* remove unused import

* Fix test

* Forgot a method

* missing test

* Trigger CI

* naming update

* Rebase

* Trigger CI

* Add a serving method

* Add albert

* Add serving for BERT and BART

* Add more models

* Finish the serving addition

* Temp fix

* Restore DPR

* Fix funnel attribute

* Fix attributes GPT2

* Fix OpenAIGPT attribute

* Fix T5 attributes

* Fix Bart attributes

* Fix TransfoXL attributes

* Add versioning

* better test

* Update template

* Fix Flaubert

* Fix T5

* Apply style

* Remove unused imports

* Deactivate extra parameters

* Remove too long test + saved_model default to False

* Ignore the saved model test for some models

* Fix some inputs

* Fix mpnet serving

* Trigger CI

* Address all comments

* add tests

* make style and fix bart bug

* fix bart past key value edge case

* correct tf bart test

* fix gpt2 tf

* fix t5 test

* Fix T5 for graphe compilation+execution

* Fix BART

* Fix import

* Fix naming

* fix attribute name

* Oops

* fix import

* fix tests

* fix tests

* Update test

* Add mising import

* Address Patrick's comments

* Style

* Address Patrick's comment

* Resize the biases in same time than the embeddings

* Trigger CI

* Biases are not reset anymore

* Remove get_output_embeddings + better LM model detection in generation utils

* Apply style

* First test on BERT

* Update docstring + new name

* Apply the new resizing logic to all the models

* fix tests

* Apply style

* Update the template

* Fix naming

* Fix naming

* Apply style

* Apply style

* Remove unused import

* Revert get_output_embeddings

* Trigger CI

* Update num parameters

* Restore get_output_embeddings in TFPretrainedModel and add comments

* Style

* Add decoder resizing

* Style

* Fix tests

* Separate bias and decoder resize

* Fix tests

* Fix tests

* Apply style

* Add bias resizing in MPNet

* Trigger CI

* Apply style

* Add copyright everywhere missing

* Style

* Add T5 Encoder class for feature extraction

* fix T5 encoder add_start_docstrings indent

* update init with T5 encoder

* update init with TFT5ModelEncoder

* remove TFT5ModelEncoder

* change T5ModelEncoder order in init

* add T5ModelEncoder to transformers init

* clean T5ModelEncoder

* update init with TFT5ModelEncoder

* add TFModelEncoder for Tensorflow

* update init with TFT5ModelEncoder

* Update src/transformers/models/t5/modeling_t5.py

change output from Seq2SeqModelOutput to BaseModelOutput
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* remove encoder_outputs

1. remove encoder_outputs from the function call.
2. remove the encoder_outputs If statement.
3. remove isinstance from return_dict.

* Authorize missing decoder keys

* remove unnecessary input parameters

remove pask_key_values and use_cache

* remove use_cache

remove use_cache from the forward method

* add doctoring for T5 encoder

add doctoring for T5 encoder with T5_ENCODER_INPUTS_DOCSTRING

* change return_dict to dot access

* add T5_ENCODER_INPUTS_DOCSTRING for TF T5

* change TFT5Encoder output type to BaseModelOutput

* remove unnecessary parameters for TFT5Encoder

* remove unnecessary if statement

* add import BaseModelOutput

* fix BaseModelOutput typo to TFBaseModelOutput

* update T5 doc with T5ModelEncoder

* add T5ModelEncoder to tests

* finish pytorch

* finish docs and mt5

* add mtf to init

* fix init

* remove n_positions

* finish PR

* Update src/transformers/models/mt5/modeling_mt5.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update src/transformers/models/t5/modeling_t5.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update src/transformers/models/t5/modeling_tf_t5.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update src/transformers/models/mt5/modeling_tf_mt5.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* make style
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* add mt5 and t5v1_1 model

* fix tests

* correct some imports

* add tf model

* finish tf t5

* improve examples

* fix copies

* clean doc

* Use the CI to identify failing tests

* Remove from all examples and tests

* More default switch

* Fixes

* More test fixes

* More fixes

* Last fixes hopefully

* Use the CI to identify failing tests

* Remove from all examples and tests

* More default switch

* Fixes

* More test fixes

* More fixes

* Last fixes hopefully

* Run on the real suite

* Fix slow tests

* fix bug

* T5 refactor

* refactor tf

* apply sylvains suggestions