GitLab

* Fix wrong documentation about DataCollator padding defaults

* Fix styling

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

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

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

* fix

* fix

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

* feat: filter try/except

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

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

* fix auto 2

* fix auto 2

* fix task guide issue

* fix

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

upgrade to large VM
Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

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

* faster forward following what is done for images

* add missing licence

* rework is_pipeline_test

* bring back 3 tests

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

* intial test of inputs

* added test for generation

* remove asserts

* fixed test

* Update tests/models/time_series_transformer/test_modeling_time_series_transformer.py
Co-authored-by: NielsRogge <48327001+NielsRogge@users.noreply.github.com>

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

* Make ZeroShotImageClassificationPipeline faster

The pipeline makes separate calls to model for each candidate label.
This commit combines all labels into one call.
Original code takes more that 60 seconds to process one image and 1000
candidate labels. Updated code takes less than 2 seconds.

* implement batching

* code formatting

* Creating an even faster zero-shot-image-classifiction.

Unfortunately super tailored towards CLIP.
Co-Authored-By: Yessen Kanapin <yessen@deepinfra.com>

* Quality.

* Cleanup.

* Order different on the CI it seems.

* Cleanup.

* Quality.

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Co-authored-by: Yessen Kanapin <yessen@deepinfra.com>

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

* fix

* add to tests

* style and quality

* add missing

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

* [WIP] whisper refacto to support language output.

* Handling merges.

* A bit more cleanup and comments.

* Many improvements.

Lots of details everywhere.

* Cleanup old code and tests.

* Handle lone timestamp tokens (just recover when something bad happens).

* Adding return_language example.

* No ffmpeg.

* Hmm.

* Some corrections.

* Both fast and slow.

* New black.

* Update src/transformers/models/whisper/tokenization_whisper.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Update src/transformers/models/whisper/tokenization_whisper.py
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Remove print.

* Undoing tests modifications.

* Smaller test modifications.

* Rename.

* Remove maxDiff.

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Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Make schedulers picklable by making lr_lambda fns global

* add unused _get_constant_schedule_lr_lambda arg

* remove unneeded _get_constant_schedule_lr_lamda

* add test

* make style

* rebase, remove torch dep, put lambda back

* repo-consistency and style

* decoder forward pass is working

* no model has forward pass returning attentions

* decoder ngram changed to not mix batch size

* current basic forward pass returns identical result

* passed test_model attentions

* passed test_encoder_decoder_model_generate

* passed test_headmasking

* removed old block

* removed comments bug/fixme

* removed bug comments

* applied styling

* applied fix-copies

* applied ngram forward comments

* corrected dimension notation

* applied styling and comment fixes

* changed asserts for raise ValueError

* changed question gen test

* updated hidden_states integration test

* applied styling

* add new test

* fix after new test

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

* Mark pipeline tests to skip them easily

* Mark the mixin as pipeline test

* Update src/transformers/testing_utils.py
Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>

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Co-authored-by: Yih-Dar <2521628+ydshieh@users.noreply.github.com>

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: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* add deprecation warning

* remove pos ids from args docstirng

* fix failing test

* add `zero_mean_unit_var_norm` function

* normalize before MEL computation

* fixup

* add simple test

* quality

* Update tests/models/whisper/test_feature_extraction_whisper.py
Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>

* fixup

* use attention masks if padding was applied

* Update based on review
Co-authored-by: bofeng huang <bofenghuang7@gmail.com>

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Co-authored-by: Sanchit Gandhi <93869735+sanchit-gandhi@users.noreply.github.com>
Co-authored-by: bofeng huang <bofenghuang7@gmail.com>

* Confusing documentation in T5

* Fix onfusing documentation in T5 configuration file

* initial commit to add inputs_embeds to generation

* formatting

* Use PyAV instead of Decord

* Get frame indices

* Fix number of frames

* Update src/transformers/models/videomae/image_processing_videomae.py

* Fix up

* Fix copies

* Update timesformer doctests

* Update docstrings

add correct revision after model was overwritten

* initial commit

* update

* second batch

* style

* fix imports

* fix relative import on pipeline

* fix tests

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

* force on the same device

* fix tests

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

Co-authored-by: saswatmeher <saswatmeher@cse.iitb.ac.in>

Adds the ALIGN model to transformers. ALIGN is introduced in "Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision" by Chao Jia, Yinfei Yang, Ye Xia, Yi-Ting Chen, Zarana Parekh, Hieu Pham, Quoc V. Le, Yunhsuan Sung, Zhen Li, Tom Duerig.

* Temporary commit to stash everything so far

* Temporary commit to stash everything so far

* stash commit

* Refactor from_pretrained

* Fix final test, make fixup

* Update dummies

* Add model to TEST_FILES_WITH_NO_COMMON_TESTS

* Update src/transformers/models/vision_text_dual_encoder/modeling_tf_vision_text_dual_encoder.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update src/transformers/models/vision_text_dual_encoder/modeling_tf_vision_text_dual_encoder.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update src/transformers/models/vision_text_dual_encoder/modeling_tf_vision_text_dual_encoder.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update src/transformers/models/vision_text_dual_encoder/modeling_tf_vision_text_dual_encoder.py
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Add TFVisionTextDualEncoder to utils/documentation_tests.txt

* make fixup

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Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>