GitLab

* Rewrite push_to_hub to use upload_files

* Adapt the doc a bit

* Address review comments and clean doc

* add LUKE models for downstream tasks

* add new LUKE models to docs

* fix typos

* remove commented lines

* exclude None items from tuple return values

* Bloom model can now be traced

* Bloom traced model can be torch scripted and serialized

* Bloom can be traced with variable keyword arguments

* Enable XLNet support

* Disable XLNet for now

* Preliminary work on tokenizers

* Quality + fix tests

* Treat processors

* Fix pad

* Remove all uses of  in tests, docs and examples

* Replace all as_target_tokenizer

* Fix tests

* Fix quality

* Update examples/flax/image-captioning/run_image_captioning_flax.py
Co-authored-by: amyeroberts <amy@huggingface.co>

* Style
Co-authored-by: amyeroberts <amy@huggingface.co>

* Add files generated using transformer-cli add-new-model-like command

* Add changes for swinv2 attention and forward method

* Add fixes

* Add modifications for weight conversion and remaining args in swin model

* Add changes for patchmerging

* Add changes for SwinV2selfattention

* Update conversion script

* Add final fixes for the swin_v2 model

* Add changes for conversion script for pretrained window size case

* Add pretrained window size value from config in SwinV2Encoder class

* Make fixup

* Add swinv2 to models_not_in_readme to utils/check_copies.py

* Modify Swinv2v2 to Swin Transformer V2

* Remove copied from, to run make fixup command

* Add updates to swinv2tf from main branch

* Add pretrained_window_size to config, to make tests pass

* Add modified weights from nandwalritik profile for swinv2

* Update model weights from swinv2 from nandwalritik profile

* Add fix for build_pr_documentation CI fix

* Add fixes for weight conversion

* Add change to make input with padding work

* Add fixes for test cases

* Add few changes from swin to swinv2 to pass test cases

* Remove tests for tensorflow as swinv2 for TF is not added yet

* Overide test_pt_tf_model_equivalence function as TF implementation for swinv2 is not added yet

* Add modeling_tf_swinv2 to _ignore_modules as test file is removed for this one right now.

* Update docs url for swinv2 in README.md
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Undo changes for check_repo

* Update url in readme.md

* Remove overrided function to test pt_tf_model_equivalence

* Remove TF model imports for Swinv2 as its not implemented in this PR

* Add changes for index.mdx

* Add swinv2 papers link,abstract and contributors details

* Rename cpb_mlp to continous_position_bias_mlp

* Add tips for swinv2 model

* Update src/transformers/models/swinv2/configuration_swinv2.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/swinv2/configuration_swinv2.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Fix indentation for docstring example in src/transformers/models/swinv2/configuration_swinv2.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update import order in src/transformers/models/swinv2/configuration_swinv2.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Add copyright statements in weights conversion script.
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Remove Swinv2 from models_not_in_readme

* Reformat code

* Remove TF implementation file for swinv2

* Update start docstring.
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Add changes for docstring

* Update orgname for weights to microsoft

* Remove to_2tuple function

* Add copied from statements wherever applicable

* Add copied from to Swinv2ForMaskedImageModelling class

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

* Add unittest.skip(with reason.) for test_inputs_embeds test case.
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Add updates for test_modeling_swinv2.py

* Add @unittest.skip() annotation for clarity to create_and_test_config_common_properties function

* Add continuous_position_bias_mlp parameter to conversion script

* Add test for testing masked_image_modelling for swinv2

* Update Swinv2 to Swin Transformer v2 in docs/source/en/model_doc/swinv2.mdx
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update Swinv2 to Swin Transformer v2 in docs/source/en/model_doc/swinv2.mdx
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update docs/source/en/model_doc/swinv2.mdx
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update docs/source/en/model_doc/swinv2.mdx
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Add suggested changes

* Add copied from to forward methods of Swinv2Stage and Swinv2Encoder

* Add push_to_hub flag to weight conversion script

* Change order or Swinv2DropPath class

* Add id2label mapping for imagenet 21k

* Add updated url for SwinV2 functions and classes used in implementation

* Update input_feature dimensions format, mentioned in comments.
Co-authored-by: Alara Dirik <8944735+alaradirik@users.noreply.github.com>

* Add suggested changes for modeling_swin2.py

* Update docs

* Remove create_and_test_config_common_properties function, as test_model_common_attributes is sufficient.

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

* Add changes for making Nit objects in code style

* Add suggested changes

* Add suggested changes for test_modelling_swinv2

* make fix-copies

* Update docs/source/en/model_doc/swinv2.mdx
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>
Co-authored-by: Alara Dirik <8944735+alaradirik@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* fix owlvit test assertion errors

* fix gpu test error

* remove redundant lines

* fix styling

* Fixes torch jit tracing for LayoutLMv2 model.
Pytorch seems to reuse memory for input_shape which caused a mismatch in shapes later in the forward pass.

* Fixed code quality

* avoid unneeded allocation of vector for shape

* Add ViltForTokenClassification e.g. for Named-Entity-Recognition (NER)

* Add ViltForTokenClassification e.g. for Named-Entity-Recognition (NER)

* provide classifier only text hidden states

* add test_for_token_classification

* Update src/transformers/models/vilt/modeling_vilt.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/vilt/modeling_vilt.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/vilt/modeling_vilt.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Update src/transformers/models/vilt/modeling_vilt.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* add test_for_token_classification
Co-authored-by: gfuchs <gfuchs@ebay.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Add serving_output and serving methods to some vision models

* Add serving outputs for DeiT

* Don't convert hidden states - differing shapes

* Make saveable

* Fix up

* Make swin saveable

* Add in tests

* Fix funnel tests (can't convert to tensor)

* Fix numpy call

* Tidy up a bit

* Add in hidden states - resnet

* Remove numpy

* Fix failing tests - tensor shape and skipping tests

* Remove duplicated function

* PR comments - formatting and var names

* PR comments
Add suggestions made by Joao Gante:
* Use tf.shape instead of shape_list
* Use @tooslow decorator on tests
* Simplify some of the logic

* PR comments
Address Yih-Dar Sheih comments - making tensor names consistent and make types float

* Types consistent with docs; disable test on swin (slow)

* CI trigger

* Change input_features to float32

* Add serving_output for segformer

* Fixup
Co-authored-by: Amy Roberts <amyeroberts@users.noreply.github.com>

* add owlvit model skeleton

* add class and box predictor heads

* convert modified flax clip to pytorch

* fix box and class predictors

* add OwlViTImageTextEmbedder

* convert class and box head checkpoints

* convert image text embedder checkpoints

* add object detection head

* fix bugs

* update conversion script

* update conversion script

* fix q,v,k,out weight conversion conversion

* add owlvit object detection output

* fix bug in image embedder

* fix bugs in text embedder

* fix positional embeddings

* fix bug in inference mode vision pooling

* update docs, init tokenizer and processor files

* support batch processing

* add OwlViTProcessor

* remove merge conflicts

* readd owlvit imports

* fix bug in OwlViTProcessor imports

* fix bugs in processor

* update docs

* fix bugs in processor

* update owlvit docs

* add OwlViTFeatureExtractor

* style changes, add postprocess method to feature extractor

* add feature extractor and processor tests

* add object detection tests

* update conversion script

* update config paths

* update config paths

* fix configuration paths and bugs

* fix bugs in OwlViT tests

* add import checks to processor

* fix docs and minor issues

* fix docs and minor issues

* fix bugs and issues

* fix bugs and issues

* fix bugs and issues

* fix bugs and issues

* update docs and examples

* fix bugs and issues

* update conversion script, fix positional embeddings

* process 2D input ids, update tests

* fix style and quality issues

* update docs

* update docs and imports

* update OWL-ViT index.md

* fix bug in OwlViT feature ext tests

* fix code examples, return_dict by default

* return_dict by default

* minor fixes, add tests to processor

* small fixes

* add output_attentions arg to main model

* fix bugs

* remove output_hidden_states arg from main model

* update self.config variables

* add option to return last_hidden_states

* fix bug in config variables

* fix copied from statements

* fix small issues and bugs

* fix bugs

* fix bugs, support greyscale images

* run fixup

* update repo name

* merge OwlViTImageTextEmbedder with obj detection head

* fix merge conflict

* fix merge conflict

* make fixup

* fix bugs

* fix bugs

* add additional processor test

* add: segformer utils and img. classification.

* add: segmentation layer.

* feat: working implementation of segformer.

* chore: remove unused variable.

* add test, remaining modifications.

* remove: unnecessary files.

* add: rest of the files.
Co-authored-by: matt <rocketknight1@gmail.com>

* chore: remove ModuleList comment.

* chore: apply make style.

* chore: apply make fixup-copies.

* add  to check_repo.py

* add decode head to IGNORE_NON_TESTED

* chore: run make style.

* chore: PR comments.

* chore: minor changes to model doc.

* tests: reduction across samples.

* add a note on the space.

* sort importats.

* fix: reduction in loss computation.

* chore: align loss function with that of NER.

* chore: correct utils/documentation_tests.txt
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* chore: simplify the interpolation of logits in loss computation.

* chore: return transposed logits when return_dict=False.

* chore: add link to the tf fine-tuning repo.

* address pr comments.

* address niels's comments.

* remove from_pt=True since tf weights are in.

* remove comment from pt model.

* address niels's comments.
Co-authored-by: matt <rocketknight1@gmail.com>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

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

* 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