GitLab

* Update modeling tests

* update tokenization test

* typo

* nit

* fix expected attention outputs

* Apply suggestions from code review
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* Update tests from review
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* remove problematics kwargs passed to the padding function
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* update relative positional embedding

* make fix copies

* add `use_cache` to list of arguments

* fixup

* 1line fucntion

* add `test_decoder_model_past_with_large_inputs_relative_pos_emb`

* add relative pos embedding test for more models

* style

* fix slow test

* Update tests/models/roc_bert/test_modeling_roc_bert.py

* First draft

* Remove scatter dependency

* Add require_torch

* update vectorized sum test, add clone call

* remove artifacts

* fix style

* fix style v2

* remove "scatter" mentions from the code base

* fix isort error
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MacBook-Pro.local>
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* add model files etc for MobileNetV2

* rename files for MobileNetV1

* initial implementation of MobileNetV1

* fix conversion script

* cleanup

* write docs

* tweaks

* fix conversion script

* extract hidden states

* fix test cases

* make fixup

* fixup it all

* rename V1 to V2

* fix checkpoints

* fixup

* implement first block + weight conversion

* add remaining layers

* add output stride and dilation

* fixup

* add tests

* add deeplabv3+ head

* a bit of fixup

* finish deeplab conversion

* add link to doc

* fix issue with JIT trace

in_height and in_width would be Tensor objects during JIT trace, which caused Core ML conversion to fail on the remainder op. By making them ints, the result of the padding calculation becomes a constant value.

* cleanup

* fix order of models

* fix rebase error

* remove main from doc link

* add image processor

* remove old feature extractor

* fix converter + other issues

* fixup

* fix unit test

* add to onnx tests (but these appear broken now)

* add post_process_semantic_segmentation

* use google org

* remove unused imports

* move args

* replace weird assert

* Apply fix

* Fix test

* Remove another argument which is not used

* Fix pipeline test

* Add argument back, add deprecation warning

* Add warning add other location

* Use warnings instead

* Add num_channels to config
Co-authored-by: Niels Rogge <nielsrogge@Nielss-MBP.localdomain>

* [processor] Add 'model input names' property

* add test

* no f string

* add generic property method to mixin

* copy to multimodal

* copy to vision

* tests for all audio

* remove ad-hoc tests

* style

* fix flava test

* fix test

* fix processor code

* TrOCR processor uses an image processor

* Update VisionEncoderDecoder

* Add feature_extractor_class property

* move generation_*.py src files into generation/*.py

* populate generation.__init__ with lazy loading

* move imports and references from generation.xxx.object to generation.object

* Attempting to test automatically the `_keys_to_ignore`.

* Style.

* First fix pass.

* Moving test on its own.

* Another batch.

* Second round removing BatchNorm

* Fixing layoutlmv{2,3} + support older Python.

* Disable miss missing warning.

* Removing dodgy additions.

* Big pass.

* mbart.

* More corrections.

* Fixup.

* Updating test_correct_missing_keys

* Add escape hatch for when the head has no extra params so doesn't need

the missing keys check.

* Fixing test.

* Greener.

* Green ! (except for weird splinter bug).

* Adding a test about `named_parameters` usage.

* Shorten message.

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

* After rebase modifications.

* More explicit condition checking.

* Fixing slow tests issues.

* Remove extra pdb.

* Remove print.

* Attempt to make failure consistent + fixing roc_bert.

* Removing the seed  (all tests passing with it).
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

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

* AutoImageProcessor skeleton

* Update references

* Add mapping in init

* Add model image processors to __init__ for importing

* Add AutoImageProcessor tests

* Fix up

* Image Processor documentation

* Remove pdb

* Update docs/source/en/model_doc/mobilevit.mdx

* Update docs

* Don't add whitespace on json files

* Remove fixtures

* Move checking model config down

* Fix up

* Add check for image processor

* Remove FeatureExtractorMixin in docstrings

* Rename model_tmpfile to config_tmpfile

* Don't make None if not in image processor map

* add roc_bert

* update roc_bert readme

* code style

* change name and delete unuse file

* udpate model file

* delete unuse log file

* delete tokenizer fast

* reformat code and change model file path

* add RocBertForPreTraining

* update docs

* delete wrong notes

* fix copies

* fix make repo-consistency error

* fix files are not present in the table of contents error

* change RocBert -> RoCBert

* add doc, add detail test
Co-authored-by: weiweishi <weiweishi@tencent.com>

* Add first draft

* Update conversion script

* Improve conversion script

* Improve conversion script some more

* Add conditional embeddings

* Add initial decoder

* Fix activation function of decoder

* Make decoder outputs match original implementation

* Make decoder outputs match original implementation

* Add more copied from statements

* Improve model outputs

* Fix auto tokenizer file

* Fix more tests

* Add test

* Improve README and docs, improve conditional embeddings

* Fix more tests

* Remove print statements

* Remove initial embeddings

* Improve conversion script

* Add interpolation of position embeddings

* Finish addition of interpolation of position embeddings

* Add support for refined checkpoint

* Fix refined checkpoint

* Remove unused parameter

* Improve conversion script

* Add support for training

* Fix conversion script

* Add CLIPSegFeatureExtractor

* Fix processor

* Fix CLIPSegProcessor

* Fix conversion script

* Fix most tests

* Fix equivalence test

* Fix README

* Add model to doc tests

* Use better variable name

* Convert other checkpoint as well

* Update config, add link to paper

* Add docs

* Update organization

* Replace base_model_prefix with clip

* Fix base_model_prefix

* Fix checkpoint of config

* Fix config checkpoint

* Remove file

* Use logits for output

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

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

* Add contrastive search

* Update defaults and logic to match old FE

* Use docker run rest values

* POC

* For more CLIP-like models
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Fix esm lm head test

* make fixup

* [Whisper Tokenizer] Make more user-friendly

* use property

* make indexing rigorous

* small clean-up

* tests

* skip seq2seq tests

* remove multilingual arg

* reorder args

* collapse to one function
Co-authored-by: ArthurZucker <arthur@huggingface.co>

* option to override attributes
Co-authored-by: ArthurZucker <arthur@huggingface.co>

* add to docs

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

* make comment more clear
Co-authored-by: sgugger <sylvain@huggingface.co>

* don't add special tokens in get_decoder_prompt_ids

* add test for set_prefix_tokens
Co-authored-by: ArthurZucker <arthur@huggingface.co>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: sgugger <sylvain@huggingface.co>

🚨 🚨 🚨 Fix Issue 15003: SentencePiece Tokenizers Not Adding Special Tokens in `convert_tokens_to_string` (#15775)

* Add test for SentencePiece not adding special tokens to strings

* Add SentencePieceStringConversionMixin to fix issue 15003

* Fix conversion from tokens to string for most SentencePiece tokenizers

Tokenizers fixed:
- AlbertTokenizer
- BarthezTokenizer
- CamembertTokenizer
- FNetTokenizer
- M2M100Tokenizer
- MBart50Tokenizer
- PegasusTokenizer
- Speech2TextTokenizer

* Fix MarianTokenizer, adjust SentencePiece test to accomodate vocab

* Fix DebertaV2Tokenizer

* Ignore LayoutXLMTokenizer in SentencePiece string conversion test

* Run 'make style' and 'make quality'

* Clean convert_tokens_to_string test

Instead of explicitly ignoring LayoutXLMTokenizer in the test,
override the test in LayoutLMTokenizationTest and do nothing in it.

* Remove commented out code

* Improve robustness of convert_tokens_to_string test

Instead of comparing lengths of re-tokenized text and input_ids,
check that converting all special tokens to string yields a string
with all special tokens.

* Inline and remove SentencePieceStringConversionMixin

The convert_tokens_to_string method is now implemented
in each relevant SentencePiece tokenizer.

* Run 'make style' and 'make quality'

* Revert removal of space in convert_tokens_to_string

* Remove redundant import

* Revert test text to original

* Uncomment the lowercasing of the reverse_text variable

* Mimic Rust tokenizer behavior for tokenizers

- Albert
- Barthez
- Camembert
- MBart50
- T5

* Fix accidentally skipping test in wrong tokenizer

* Add test for equivalent Rust and slow tokenizer behavior

* Override _decode in BigBirdTokenizer to mimic Rust behavior

* Override _decode in FNetTokenizer to mimic Rust behavior

* Override _decode in XLNetTokenizer to mimic Rust behavior

* Remove unused 're' import

* Update DebertaV2Tokenizer to mimic Rust tokenizer

* Deberta tokenizer now behaves like Albert and its `convert_tokens_to_string` is not tested.

* Ignore problematic tests in Deberta V2

* Add comment on why the Deberta V2 tests are skipped

* part 1

* part 2

* part 3

* fix

* For CANINE

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

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

* Add CLIP image processor

* Crop size as dict too

* Update warning

* Actually use logger this time

* Normalize doesn't change dtype of input

* Add perceiver image processor

* Tidy up

* Add DPT image processor

* Add Vilt image processor

* Tidy up

* Add poolformer image processor

* Tidy up

* Add LayoutLM v2 and v3 imsge processors

* Tidy up

* Add Flava image processor

* Tidy up

* Add deit image processor

* Tidy up

* Add ConvNext image processor

* Tidy up

* Add levit image processor

* Add segformer image processor

* Add in post processing

* Fix up

* Add ImageGPT image processor

* Fixup

* Add mobilevit image processor

* Tidy up

* Add postprocessing

* Fixup

* Add VideoMAE image processor

* Tidy up

* Add ImageGPT image processor

* Fixup

* Add ViT image processor

* Tidy up

* Add beit image processor

* Add mobilevit image processor

* Tidy up

* Add postprocessing

* Fixup

* Fix up

* Fix flava and remove tree module

* Fix image classification pipeline failing tests

* Update feature extractor in trainer scripts

* Update pad_if_smaller to accept tuple and int size

* Update for image segmentation pipeline

* Update src/transformers/models/perceiver/image_processing_perceiver.py
Co-authored-by: Alara Dirik <8944735+alaradirik@users.noreply.github.com>

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

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

* PR comments - docstrings; remove accidentally added resize; var names

* Update docstrings

* Add exception if size is not in the right format

* Fix exception check

* Fix up

* Use shortest_edge in tuple in script
Co-authored-by: Alara Dirik <8944735+alaradirik@users.noreply.github.com>
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

* Use beam search functionality; Add extra outputs and test

* Add full tests for contrastive search

* Add error message on unconventional cache format

* initial commit

* First draft that gets outputs without crashing!

* Add all the ported openfold dependencies

* testing

* Restructure config files for ESMFold

* Debugging to find output discrepancies

* Mainly style

* Make model runnable without extra deps

* Remove utils and merge them to the modeling file

* Use correct gelu and remove some debug prints

* More cleanup

* Update esm docs

* Update conversion script to support ESMFold properly

* Port some top-level changes from ESMFold repo

* Expand EsmFold docstrings

* Make attention_mask optional (default to all 1s)

* Add inference test for ESMFold

* Use config and not n kwargs

* Add modeling output class

* Remove einops

* Remove chunking in ESM FFN

* Update tests for ESMFold

* Quality

* REpo consistency

* Remove tree dependency from ESMFold

* make fixup

* Add an error in case my structure map function breaks later

* Remove needless code

* Stop auto-casting the LM to float16 so CPU tests pass

* Stop auto-casting the LM to float16 so CPU tests pass

* Final test updates

* Split test file

* Copyright and quality

* Unpin PyTorch to see built doc

* Fix config file to_dict() method

* Add some docstrings to the output

* Skip TF checkpoint tests for ESM until we reupload those

* make fixup

* More docstrings

* Unpin to get even with main

* Flag example to write
Co-authored-by: Sylvain Gugger <Sylvain.gugger@gmail.com>

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

* Add postprocessing methods

* Update docs

* Add fix

* Add test

* Add test for deformable detr postprocessing

* Add post processing methods for segmentation

* Update code examples

* Add post_process to make the pipeline work

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

* Support segformer fx

* Add fx_compatible attribute to test_modeling_segformer.py

* Update glpn model (fx support)

glpn model was copied from segformer.

* Update utils/fx.py | add semantic-segmentation

for SegformerForSemanticSegmentation model

* Fix minor import order(isort)

* Add random input generation for segformer fx
Co-authored-by: noelbird <lduldu00228@gmail.com>

* Fix tests when running on GPU

* Fix tests that require mp.set_start_method

* Add pegasus_x

* ViTMSN

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

* Support for Vilt in v1.9

* Skip if not higher or equal than 1.10

* Move test :)

* I am bad at python

* Update expected values

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

* Run some TF Whisper tests in subprocesses to avoid GPU OOM
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

* Fix panoptic segmentation and pipeline
* Update ImageSegmentationPipeline tests and reenable test_small_model_pt
* Resolve backward compatibility issues

* support sentencepiece for bertjapanesetokenizer

* add test vocab file for sentencepiece, bertjapanesetokenizer

* make BasicTokenizer be identical to transformers.models.bert.tokenization_bert.BasicTokenizer

* fix missing of \n in comment

* fix init argument missing in tests

* make spm_file be optional, exclude spiece.model from tests/fixtures, and add description comments

* make comment length less than 119

* apply doc style check