GitLab

* Adding OPTForSeqClassification class

* Fix import issues

* Add documentation for optforseqclassification

* Remove checkout

* fix failing tests

* fix typo

* Fix code formatting

* Incorporating the PR feedbacks

* Incorporate PR Feedbacks

* Fix failing test and add new test for multi label setup

* Fix formatting issue

* Fix failing tests

* Fix formatting issues

* Fix failing tests

* Fix failing tests

* Fix failing tests

* Fix failing tests

* PR feedback

* Fix TF GPT-J tests

* add try/finally block

* Initial work

* More work

* Add tests for custom pipelines on the Hub

* Protect import

* Make the test work for TF as well

* Last PyTorch specific bit

* Add documentation

* Style

* Title in toc

* Bad names!

* Update docs/source/en/add_new_pipeline.mdx
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>

* Auto stash before merge of "custom_pipeline" and "origin/custom_pipeline"

* Address review comments

* Address more review comments

* Update src/transformers/pipelines/__init__.py
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>
Co-authored-by: Lysandre Debut <lysandre.debut@reseau.eseo.fr>

* add first generation tutorial

* [from_pretrained] Allow loading models from subfolders

* remove gen file

* add doc strings

* allow download from subfolder

* add tests

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* apply comments

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

* minor fixes

- add correct revision
- corrected dosctring for test
- removed a test

* contrib credits
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
Co-authored-by: Nouamane Tazi <nouamane98@gmail.com>
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>
Co-authored-by: Nouamane Tazi <nouamane98@gmail.com>

Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* fix expected loss values
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

Co-authored-by: Guilhem Chéron <guilhemc@authentifier.com>

* NLLB tokenizer

* Apply suggestions from code review - Thanks Stefan!
Co-authored-by: Stefan Schweter <stefan@schweter.it>

* Final touches

* Style :)

* Update docs/source/en/model_doc/nllb.mdx
Co-authored-by: Stefan Schweter <stefan@schweter.it>

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* PR reviews

* Auto models
Co-authored-by: Stefan Schweter <stefan@schweter.it>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Adding support for `device_map` directly in `pipeline(..)` function.

* Updating the docstring.

* Adding a better docstring

* Put back type hints.

* Blacked. (`make fixup` didn't work ??!!)

* Initial TF DeiT implementation

* Fix copies naming issues

* Fix up + docs

* Properly same main layer

* Name layers properly

* Initial TF DeiT implementation

* Fix copies naming issues

* Fix up + docs

* Properly same main layer

* Name layers properly

* Fixup

* Fix import

* Fix import

* Fix import

* Fix weight loading for tests whilst not on hub

* Add doc tests and remove to_2tuple

* Add back to_2tuple
Removing to_2tuple results in many downstream changes needed because of the copies checks

* Incorporate updates in Improve vision models #17731 PR

* Don't hard code num_channels

* Copy PyTorch DeiT embeddings and remove pytorch operations with mask

* Fix patch embeddings & tidy up

* Update PixelShuffle to move logic into class layer

* Update doc strings - remove PT references

* Use NHWC format in internal layers

* Fix up

* Use linear activation layer

* Remove unused import

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Move dataclass to top of file

* Remove from_pt now weights on hub

* Fixup
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Amy Roberts <amyeroberts@users.noreply.github.com>

* enable fx2trt

* Update perf_train_gpu_one.mdx

* Update perf_train_gpu_one.mdx

* add lib check

* update

* format

* update

* fix import check

* fix isort

* improve doc

* refactor ctx manager

* fix isort

* black format

* isort fix

* fix format

* update args

* update black

* cleanups

* Update perf_train_gpu_one.mdx

* code refactor

* code refactor to init

* remove redundancy

* isort

* replace self.args with args
Co-authored-by: Stas Bekman <stas@stason.org>

* Make sharded checkpoints work in offline mode

* Add test

* enhance ipex import

* refine codes

* refine style

* add link

* style
Co-authored-by: Stas Bekman <stas@stason.org>

* fix tolerance for a bloom slow test

* enhance alibi padding

- get rid of for loops
- deals better with padded batched input
- avoid useless cpu/gpu communication when creating alibi
Co-authored-by: justheuristic <justheuristic@gmail.com>

* optimize attention mask

* fix scaled softmax limit values

* optimize building alibi tensor
Co-authored-by: Younes Belkada <younesbelkada@users.noreply.github.com>

* fix attention_mask shape when it's None

* minor fixes

- fix docstring + arg names

* remove colons in docstring

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

* apply suggestion

* remove unsued arg

* refactor a bit

- use [:, None] for consistency

* refactor attention block
Co-authored-by: Nouamane Tazi <nouamane98@gmail.com>

* quick fixes

* first attempt

* refactor attention block and fix all tests except "test_simple_generation"

- added comments to better explain attention block

* remove debug lines and add TODO comment

* change `torch.bmm` to `torch.baddbmm`
- fixes `test_simple_generation`but breaks `test_batch_generation_padd`

* styling

* all tests are passing now
- use `bmm`
- add explanation for `allow_fp16_reduced_precision_reduction`
Co-authored-by: Younes Belkada <younesbelkada@users.noreply.github.com>

* styling
Co-authored-by: Younes Belkada <younesbelkada@users.noreply.github.com>

* fix support for accelerate
Co-authored-by: Younes Belkada <younesbelkada@users.noreply.github.com>

* Apply suggestions from code review
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* remove attn softmax in fp32

* refactor comments

* refactor a bit

- remove warning message
- remove print on test

* refer to pytorch t5

* change the slow tests

- do the tests in fp32
- remove some comments
- keep large comments

* update expected output for `test_simple_generation`
- we now test using fp32

* make style + change comments a bit

* fix dtype padd test
Co-authored-by: justheuristic <justheuristic@gmail.com>
Co-authored-by: Nouamane Tazi <nouamane98@gmail.com>
Co-authored-by: Younes Belkada <younesbelkada@users.noreply.github.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Fix some typos.
Signed-off-by: Yulv-git <yulvchi@qq.com>

* Fix typo.
Signed-off-by: Yulv-git <yulvchi@qq.com>

* make fixup.

* Make Trainer.predict call on_evaluate (#17952)

* Add on_predict

* Small fix

* Small and different fix

* Add tests

Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>

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

* get the right slicing index for position_bias

* Return scalar losses instead of per-sample means

* Make loss shape (1,) instead of scalar

* Allow scalar losses in test_loss_computation

* Allow scalar losses in test_loss_computation

* Allow scalar losses in test_loss_computation

* Remove XLA loss function for RAG

* Rought TF conversion outline

* Tidy up

* Fix padding differences between layers

* Add back embedder - whoops

* Match test file to main

* Match upstream test file

* Correctly pass and assign image_size parameter
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Add in MainLayer

* Correctly name layer

* Tidy up AdaptivePooler

* Small tidy-up

More accurate type hints and remove whitespaces

* Change AdaptiveAvgPool

Use the AdaptiveAvgPool implementation by @Rocketknight1, which correctly pools if the output shape does not evenly divide by input shape c.f. https://github.com/huggingface/transformers/pull/17554/files/9e26607e22aa8d069c86b50196656012ff0ce62a#r900109509

Co-authored-by: From: matt <rocketknight1@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Use updated AdaptiveAvgPool
Co-authored-by: matt <rocketknight1@gmail.com>

* Make AdaptiveAvgPool compatible with CPU

* Remove image_size from configuration

* Fixup

* Tensorflow -> TensorFlow

* Fix pt references in tests

* Apply suggestions from code review - grammar and wording
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Add TFResNet to doc tests

* PR comments - GlobalAveragePooling and clearer comments

* Remove unused import

* Add in keepdims argument

* Add num_channels check

* grammar fix: by -> of
Co-authored-by: matt <rocketknight1@gmail.com>
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* Remove transposes - keep NHWC throughout forward pass

* Fixup look sharp

* Add missing layer names

* Final tidy up - remove from_pt now weights on hub
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: matt <rocketknight1@gmail.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

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

* Copy inputs to train and test step before modifying them, as this breaks things

* Add XLA tests, fix our loss functions to be XLA-compatible

* make fixup

* Update loss computation test to expect vector of per-sample losses

* Patch loss for TFLED

* Patch loss for TFAlbert

* Add a tf_legacy_loss config flag that enables old loss functions

* Stop using config.get() because it's not a dict

* Skip loss computation test for RAG because its loss is very strange and I'm afraid to rewrite it

* make fixup

* Add XLA-compatible RAG loss

* Fix dtype of loss mask for TFAlbert

* Fix test for XLNet too because it overrides the default one

* make fixup

* Fix config test

* No more depending on GPU NaN behaviour

* Add test, avoid potential zero division

* Fix test item assignment

* Fix loss computation masking test

* make fixup

* Fix dtype bugs

* [Flax] Add remat (gradient checkpointing)

* fix variable naming in test

* flip: checkpoint using a method

* fix naming

* fix class naming

* apply PVP's suggestions from code review

* make fix-copies

* fix big-bird, electra, roberta

* cookie-cutter

* fix flax big-bird

* move test to common

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

* add onnx support for BLOOM

* use TYPE_CHECKING for type annotations

* fix past_shape for bloom (different from gpt2)

* use logical_or instead of `+` for onnx support

* bigger `atol_for_validation` for larger bloom models

* copied -> taken because it's no longer an exact copy

* remove "copied from" comment
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

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

* skip some gpt_neox tests that require 80G RAM

* remove tests

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

* feat: add pipeline registry abstraction

- added `PipelineRegistry` abstraction
- updates `add_new_pipeline.mdx` (english docs) to reflect the api addition
- migrate `check_task` and `get_supported_tasks` from
  transformers/pipelines/__init__.py to
  transformers/pipelines/base.py#PipelineRegistry.{check_task,get_supported_tasks}
Signed-off-by: Aaron Pham <29749331+aarnphm@users.noreply.github.com>

* fix: update with upstream/main

chore: Apply suggestions from sgugger's code review
Signed-off-by: Aaron Pham <29749331+aarnphm@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* chore: PR updates

- revert src/transformers/dependency_versions_table.py from upstream/main
- updates pipeline registry to use global variables
Signed-off-by: Aaron Pham <29749331+aarnphm@users.noreply.github.com>

* tests: add tests for pipeline registry
Signed-off-by: Aaron Pham <29749331+aarnphm@users.noreply.github.com>

* tests: add test for output warning.
Signed-off-by: Aaron Pham <29749331+aarnphm@users.noreply.github.com>

* chore: fmt and cleanup unused imports
Signed-off-by: Aaron Pham <29749331+aarnphm@users.noreply.github.com>

* fix: change imports to top of the file and address comments
Signed-off-by: Aaron Pham <29749331+aarnphm@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>