GitLab

* Add examples telemetry

* Alternative approach

* Add to all other examples

* Add to templates as well

* Put framework separately

* Same for TensorFlow

Change config.encoder_ffn_dim -> config.decoder_ffn_dim for decoder.

* rebase and isort

* modify cookiecutter init

* fix cookiecutter auto imports

* fix clean_frameworks_in_init

* fix add_model_to_main_init

* blackify

* replace unnecessary f-strings

* update yolos imports

* fix roberta import bug

* fix yolos missing dependency

* fix add_model_like and cookiecutter bug

* fix repository consistency error

* modify cookiecutter, fix add_new_model_like

* remove stale line
Co-authored-by: Dom Miketa <dmiketa@exscientia.co.uk>

* 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>

* [FlaxBert] Add ForCausalLM

* make style

* fix output attentions

* Add RobertaForCausalLM

* remove comment

* fix fx-to-pt model loading

* remove comment

* add modeling tests

* add enc-dec model tests

* add big_bird

* add electra

* make style

* make repo-consitency

* add to docs

* remove roberta test

* quality

* amend cookiecutter

* fix attention_mask bug in flax bert model tester

* tighten pt-fx thresholds to 1e-5

* add 'copied from' statements

* amend 'copied from' statements

* amend 'copied from' statements

* quality

* add torch.no_grad when in eval mode

* make style quality

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

* begin do_init

* add params_shape_tree

* raise error if params are accessed when do_init is False

* don't allow do_init=False when keys are missing

* make shape tree a property

* assign self._params at the end

* add test for do_init

* add do_init arg to all flax models

* fix param setting

* disbale do_init for composite models

* update test

* add do_init in FlaxBigBirdForMultipleChoice

* better names and errors

* improve test

* style

* add a warning when do_init=False

* remove extra if

* set params after _required_params

* add test for from_pretrained

* do_init => _do_init

* chage warning to info

* fix typo

* add params in init_weights

* add params to gpt neo init

* add params to init_weights

* update do_init test

* Trigger CI

* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* update template

* trigger CI

* style

* style

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

* Moved functions to pytorch_utils.py

* isort formatting

* Reverted tf changes

* isort, make fix-copies

* documentation fix

* Fixed Conv1D import

* Reverted research examples file

* backward compatibility for pytorch_utils

* missing import

* isort fix

* 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 a template to add missing tokenization test

* add cookiecutter setting

* improve doc

* Update templates/adding_a_missing_tokenization_test/README.md
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
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>

* Add unpack_inputs to remaining models

* remove stray use of inputs in the templates; fix tf.debugging of attn masks

* Big file_utils cleanup

* This one still needs to be treated separately

* 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

* Updates the default branch from master to main

* Links from `master` to `main`

* Typo

* Update examples/flax/README.md
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* undo black autoformat

* minor fix to rembert forward with default

* make fix-copies, make quality

* Adding types to template model

* Removing List from the template types

* Remove `Optional` from a couple of types that don't accept `None`
Co-authored-by: matt <rocketknight1@gmail.com>

* added type hints for BART model

* make fixup, adding imports to copied files

* Adding some missing types to cookiecutter

* Adding some missing types to cookiecutter

* Adding some missing types to cookiecutter
Co-authored-by: matt <rocketknight1@gmail.com>

* Replace all deprecated `jax.ops` operations with jnp's `at`

* np to jnp scores

* suggested changes

* Remove packed past from generation_tf_utils

* update models with the new past format

* update template accordingly

* 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 wrong method name tf.concatenate

* add tests related to causal LM / decoder

* make style and quality

* clean-up

* Fix TFBertModel's extended_attention_mask when past_key_values is provided

* Fix tests

* fix copies

* More tf.int8 -> tf.int32 in TF test template

* clean-up

* Update TF test template

* revert the previous commit + update the TF test template

* Fix TF template extended_attention_mask when past_key_values is provided

* Fix some styles manually

* clean-up

* Fix ValueError: too many values to unpack in the test

* Fix more: too many values to unpack in the test

* Add a comment for extended_attention_mask when there is past_key_values

* Fix TFElectra extended_attention_mask when past_key_values is provided

* Add tests to other TF models

* Fix for TF Electra test: add prepare_config_and_inputs_for_decoder

* Fix not passing training arg to lm_head in TFRobertaForCausalLM

* Fix tests (with past) for TF Roberta

* add testing for pask_key_values for TFElectra model
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Fix model templates

* Update paths

* 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>

* use_cache = False for PT models if labels is passed

* Fix for BigBirdPegasusForConditionalGeneration

* add warning if users specify use_cache=True

* Use logger.warning instead of warnings.warn
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

fix the `tokenizer_config.json` file for the slow tokenizer when a fast version is available (#15319)

* add new test

* update test

* remove `tokenizer_file` from `additional_files_names` in `tokenization_utils_base.py`

* add `tokenizer_file` for the fast only tokenizer

* change global variables layoutxml

* remove `"tokenizer_file"` from DPR tokenizer's Global variables

* remove `tokenizer_file` from herbert slow tokenizer init

* `"tokenizer_file"` from LED tokenizer's Global variables

* remove `tokenizer_file` from mbart slow tokenizer init

* remove `tokenizer_file` from slow tokenizer template

* adapt to versioning

* adapt the `test_tokenizer_mismatch_warning` test

* clean test

* clarify `VOCAB_FILES_NAMES` in tokenization_utils_fast.py

* Revert "remove `tokenizer_file` from mbart slow tokenizer init"

This reverts commit 0dbb723fa9c7599d4640fe30b3647a74eb4a64e1.

* Revert "`"tokenizer_file"` from LED tokenizer's Global variables"

This reverts commit 5a3f879bdd651233f3d74a3d1146c34cde82b0c2.

* Revert "remove `tokenizer_file` from herbert slow tokenizer init"

This reverts commit f5e10007b7b0ec5345e015b9de7ffec72c5407fd.

* Revert "remove `"tokenizer_file"` from DPR tokenizer's Global variables"

This reverts commit da0895330bedfafc81ae3073470a9348c669f032.

* set `tokenizer_file` in super `__init__` of mbart

* Fix TF Causal LM models' returned logits

* Fix expected shape in the tests
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Fix loss calculation in TFFunnelForTokenClassification

* revert the change in TFFunnelForTokenClassification

* fix FunnelForTokenClassification loss

* fix other TokenClassification loss

* fix more

* fix more

* add num_labels to ElectraForTokenClassification

* revert the change to research projects
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* fix missing import jnp

* Fix missing jax and k=1
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Add missing __spec__ for transformers.models.auto

* Moves the __spec__-test to the UnitTest class

* Adds module_spec to all instances of _LazyModule

* Refactors an old test from pytest to unittest

* Rename compute_loss to hf_compute_loss to avoid conflicts with the new Keras method

* make style

* Adding deprecation warning to `compute_loss`

* Fix sneaky reference to compute_loss

* Replace logger.warning with warnings.warn

* Clarifying warning and deprecation timeline

* Check the repo consistency in model templates test

* Fix doc template

* Fix docstrings

* Fix last docstring