GitLab

* Output global_attentions in Longformer models

* make style

* small refactoring

* fix tests

* make fix-copies

* add for tf as well

* remove comments in test

* make fix-copies

* make style

* add docs

* make docstring pretty
Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com>

* Test TF GPU CI

* Change cache

* Fix missing torch requirement

* Fix some model tests


Style

* LXMERT

* MobileBERT

* Longformer skip test

* XLNet

* The rest of the tests

* RAG goes OOM in multi gpu setup

* YAML test files

* Last fixes

* Skip doctests

* Fill mask tests

* Yaml files

* Last test fix

* Style

* Update cache

* Change ONNX tests to slow + use tiny model

[tests|tokenizers] Refactoring pipelines test backbone - Small tokenizers improvements - General tests speedups (#7970)

* WIP refactoring pipeline tests - switching to fast tokenizers

* fix dialog pipeline and fill-mask

* refactoring pipeline tests backbone

* make large tests slow

* fix tests (tf Bart inactive for now)

* fix doc...

* clean up for merge

* fixing tests - remove bart from summarization until there is TF

* fix quality and RAG

* Add new translation pipeline tests - fix JAX tests

* only slow for dialog

* Fixing the missing TF-BART imports in modeling_tf_auto

* spin out pipeline tests in separate CI job

* adding pipeline test to CI YAML

* add slow pipeline tests

* speed up tf and pt join test to avoid redoing all the standalone pt and tf tests

* Update src/transformers/tokenization_utils_base.py
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>

* Update src/transformers/pipelines.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

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

* Update src/transformers/testing_utils.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* add require_torch and require_tf in is_pt_tf_cross_test
Co-authored-by: Sam Shleifer <sshleifer@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* half done

* doc improvement

* Cp test file

* brokedn

* broken test

* undo some mess

* ckpt

* borked

* Halfway

* 6 passing

* boom boom

* Much progress but still 6

* boom boom

* merged master

* 10 passing

* boom boom

* Style

* no t5 changes

* 13 passing

* Integration test failing, but not gibberish

* Frustrated

* Merged master

* 4 fail

* 4 fail

* fix return_dict

* boom boom

* Still only 4

* prepare method

* prepare method

* before delete classif

* Skip tests to avoid adding boilerplate

* boom boom

* fast tests passing

* style

* boom boom

* Switch to supporting many input types

* remove FIXMENORM

* working

* Fixed past_key_values/decoder_cached_states confusion

* new broken test

* Fix attention mask kwarg name

* undo accidental

* Style and reviewers

* style

* Docs and common tests

* Cleaner assert messages

* copy docs

* style issues

* Sphinx fix

* Simplify caching logic

* test does not require torch

* copy _NoLayerEmbedTokens

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

* Update tests/test_modeling_tf_bart.py
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

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

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

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

* Line length and dont document None

* Add pipeline test coverage

* assert msg

* At parity

* Assert messages

* mark slow

* Update compile test

* back in init

* Merge master

* Fix tests
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* clean T5

* fix t5 tests

* fix index typo

* fix tf common test

* fix examples

* change positional ordering for Bart and FSTM

* add signature test

* clean docs and add tests

* add docs to encoder decoder

* clean docs

* correct two doc strings

* remove sig test for TF Elektra & Funnel

* fix tf t5 slow tests

* fix input_ids to inputs in tf

* Update src/transformers/modeling_bart.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/modeling_bart.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* implement lysandre results

* make style

* fix encoder decoder typo

* fix tf slow tests

* fix slow tests

* renaming

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

* Fix #7277

* Apply style

* Add a full training pipeline test

* Apply style

* Add TF Funnel Transformer

* Proper dummy input

* Formatting

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

* Address review comments

* One review comment forgotten
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* add tf graph compile tests

* fix conflict

* remove more tf transpose statements

* fix conflicts

* fix comment typos

* move function to class function

* fix black

* fix black

* make style

* Run new isort

* More changes

* Update CI, CONTRIBUTING and benchmarks

* Move threshold up for flaky test with Electra

* Update above as well

* Test model outputs equivalence

* Fix failing tests

* From dict to kwargs

* DistilBERT

* Addressing @sgugger and @patrickvonplaten's comments

* TF outputs and test on BERT

* Albert to DistilBert

* All remaining TF models except T5

* Documentation

* One file forgotten

* TF outputs and test on BERT

* Albert to DistilBert

* All remaining TF models except T5

* Documentation

* One file forgotten

* Add new models and fix issues

* Quality improvements

* Add T5

* A bit of cleanup

* Fix for slow tests

* Style

* Fix TF Serving when output_hidden_states and output_attentions are True

* Add tests for saved model creation + bug fix for multiple choices models

* remove unused import

* Fix the input for several layers

* Fix test

* Fix conflict printing

* Apply style

* Fix XLM and Flaubert for TensorFlow

* Apply style

* Fix TF check version

* Apply style

* Trigger CI

* Test TF Flaubert + Add {XLM, Flaubert}{TokenClassification, MultipleChoice} models and tests

* AutoModels


Tiny tweaks

* Style

* Final changes before merge

* Re-order for simpler review

* Final fixes

* Addressing @sgugger's comments

* Test MultipleChoice

* [WIP] Proposal for model outputs

* All Bert models

* Make CI green maybe?

* Fix ONNX test

* Isolate ModelOutput from pt and tf

* Formatting

* Add Electra models

* Auto-generate docstrings from outputs

* Add TF outputs

* Add some BERT models

* Revert TF side

* Remove last traces of TF changes

* Fail with a clear error message

* Add Albert and work through Bart

* Add CTRL and DistilBert

* Formatting

* Progress on Bart

* Renames and finish Bart

* Formatting

* Fix last test

* Add DPR

* Finish Electra and add FlauBERT

* Add GPT2

* Add Longformer

* Add MMBT

* Add MobileBert

* Add GPT

* Formatting

* Add Reformer

* Add Roberta

* Add T5

* Add Transformer XL

* Fix test

* Add XLM + fix XLMForTokenClassification

* Style + XLMRoberta

* Add XLNet

* Formatting

* Add doc of return_tuple arg

[Almost all TF models] TF clean up: add missing CLM / MLM loss; fix T5 naming and keras compile (#5395)

* add first version of clm tf

* make style

* add more tests for bert

* update tf clm loss

* fix tests

* correct tf ner script

* add mlm loss

* delete bogus file

* clean tf auto model + add tests

* finish adding clm loss everywhere

* fix training in distilbert

* fix flake8

* save intermediate

* fix tf t5 naming

* remove prints

* finish up

* up

* fix tf gpt2

* fix new test utils import

* fix flake8

* keep backward compatibility

* Update src/transformers/modeling_tf_albert.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/modeling_tf_auto.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/modeling_tf_electra.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/modeling_tf_roberta.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/modeling_tf_mobilebert.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/modeling_tf_auto.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/modeling_tf_bert.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/modeling_tf_distilbert.py
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

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

* Cleaning TensorFlow models

Update all classes


stylr

* Don't average loss

* fix use cache

* add bart use cache

* fix bart

* finish bart

* Configure all models to use output_hidden_states as argument passed to foward()

* Pass all tests

* Remove cast_bool_to_primitive in TF Flaubert model

* correct tf xlnet

* add pytorch test

* add tf test

* Fix broken tests

* Configure all models to use output_hidden_states as argument passed to foward()

* Pass all tests

* Remove cast_bool_to_primitive in TF Flaubert model

* correct tf xlnet

* add pytorch test

* add tf test

* Fix broken tests

* Refactor output_hidden_states for mobilebert

* Reset and remerge to master
Co-authored-by: Joseph Liu <joseph.liu@coinflex.com>
Co-authored-by: patrickvonplaten <patrick.v.platen@gmail.com>

* resize token embeddings

* add tokens

* add tokens

* add tokens

* add t5 token method

* add t5 token method

* add t5 token method

* typo

* debugging input

* debugging input

* debug

* debug

* debug

* trying to set embedding tokens properly

* set embeddings for generation head too

* set embeddings for generation head too

* debugging

* debugging

* enable generation

* add base method

* add base method

* add base method

* return logits in the main call

* reverting to generation

* revert back

* set embeddings for the bert main layer

* description

* fix conflicts

* logging

* set base model as self

* refactor

* tf_bert add method

* tf_bert add method

* tf_bert add method

* tf_bert add method

* tf_bert add method

* tf_bert add method

* tf_bert add method

* tf_bert add method

* v0

* v0

* finalize

* final

* black

* add tests

* revert back the emb call

* comments

* comments

* add the second test

* add vocab size condig

* add tf models

* add tf models. add common tests

* remove model specific embedding tests

* stylish

* remove files

* stylez

* Update src/transformers/modeling_tf_transfo_xl.py

change the error.
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* adding unchanged weight test
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Support multiple choice in tf common model tests

* Add the input_embeds test

* DOC: Replace instances of ``config.output_attentions`` with function argument ``output_attentions``

* DOC: Apply Black Formatting

* Fix errors where output_attentions was undefined

* Remove output_attentions in classes per review

* Fix regressions on tests having `output_attention`

* Fix further regressions in tests relating to `output_attentions`

Ensure proper propagation of `output_attentions` as a function parameter
to all model subclasses

* Fix more regressions in `test_output_attentions`

* Fix issues with BertEncoder

* Rename related variables to `output_attentions`

* fix pytorch tests

* fix bert and gpt2 tf

* Fix most TF tests for `test_output_attentions`

* Fix linter errors and more TF tests

* fix conflicts

* DOC: Apply Black Formatting

* Fix errors where output_attentions was undefined

* Remove output_attentions in classes per review

* Fix regressions on tests having `output_attention`

* fix conflicts

* fix conflicts

* fix conflicts

* fix conflicts

* fix pytorch tests

* fix conflicts

* fix conflicts

* Fix linter errors and more TF tests

* fix tf tests

* make style

* fix isort

* improve output_attentions

* improve tensorflow
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Better None gradients handling

* Apply Style

* Apply Style

* Create a loss class per task to compute its respective loss

* Add loss classes to the ALBERT TF models

* Add loss classes to the BERT TF models

* Add question answering and multiple choice to TF Camembert

* Remove prints

* Add multiple choice model to TF DistilBERT + loss computation

* Add question answering model to TF Electra + loss computation

* Add token classification, question answering and multiple choice models to TF Flaubert

* Add multiple choice model to TF Roberta + loss computation

* Add multiple choice model to TF XLM + loss computation

* Add multiple choice and question answering models to TF XLM-Roberta

* Add multiple choice model to TF XLNet + loss computation

* Remove unused parameters

* Add task loss classes

* Reorder TF imports + add new model classes

* Add new model classes

* Bugfix in TF T5 model

* Bugfix for TF T5 tests

* Bugfix in TF T5 model

* Fix TF T5 model tests

* Fix T5 tests + some renaming

* Fix inheritance issue in the AutoX tests

* Add tests for TF Flaubert and TF XLM Roberta

* Add tests for TF Flaubert and TF XLM Roberta

* Remove unused piece of code in the TF trainer

* bugfix and remove unused code

* Bugfix for TF 2.2

* Apply Style

* Divide TFSequenceClassificationAndMultipleChoiceLoss into their two respective name

* Apply style

* Mirror the PT Trainer in the TF one: fp16, optimizers and tb_writer as class parameter and better dataset handling

* Fix TF optimizations tests and apply style

* Remove useless parameter

* Bugfix and apply style

* Fix TF Trainer prediction

* Now the TF models return the loss such as their PyTorch couterparts

* Apply Style

* Ignore some tests output

* Take into account the SQuAD cls_index, p_mask and is_impossible parameters for the QuestionAnswering task models.

* Fix names for SQuAD data

* Apply Style

* Fix conflicts with 2.11 release

* Fix conflicts with 2.11

* Fix wrongname

* Add better documentation on the new create_optimizer function

* Fix isort

* logging_dir: use same default as PyTorch
Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* remove output_past from pt

* make style

* add optional input length for gpt2

* add use cache to prepare input

* save memory in gpt2

* correct gpt2 test inputs

* make past input optional for gpt2

* finish use_cache for all models

* make style

* delete modeling_gpt2 change in test file

* correct docstring

* correct is true statements for gpt2

* split beam search and no beam search test

* fix test

* clean generate tests

* change tf t5 argument naming for TF 2.2

* correct bug in testing

* add bad words list

* make style

* add bad_words_tokens

* make style

* better naming

* make style

* fix typo

* fix conflicts

* update bart max length test

* correct spelling mistakes

* implemented model specific encode function

* fix merge conflicts

* better naming

* save intermediate state -> need to rethink strucuture a bit

* leave tf problem as it is for now

* current version

* add layers.pop

* remove ipdb

* make style

* clean return cut decoding

* remove ipdbs

* Fix restoring layers in the decoders that doesnt exists.

* push good intermediate solution for now

* fix conflicts

* always good to refuse to merge conflicts when rebasing

* fix small bug

* improve function calls

* remove unused file

* add correct scope behavior for t5_generate
Co-authored-by: Morgan Funtowicz <funtowiczmo@gmail.com>

Adding LM Head to Transfo-XL and first step to fixing problem with Adaptive Embeddings in TransfoXL (#3286)

* first commit

* work in progress

* make language generation task pass

* update to working version for LM

* delete print

* remove dead code

* make style

* change do_samples back

* None better default as boolean

* adapt do_sample to True in test example

* make style

And only run the test on TF*MainLayer classes so marked.

When supplied by Keras deserialization, the config parameter to initializers
will be a dict. So intercept it and convert to PretrainedConfig object (and
store in instance attribute for get_config to get at it) before passing to the
actual initializer. To accomplish this, and repeat as little code as possible,
use a class decorator on TF*MainLayer classes.