GitLab

* 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>

apply normal_ after assigning weight as nn.Parameter to avoid unnecessary initialization computation

* Add check for different embedding types in examples

* Correctly update summarization example

* Add an utility file to get information from test files

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

* update FSDP and add XLA-FSDP documentation

* resolving comments

* minor update

* fix xla-fsdp docs

removed BLIP mention from the troubleshooting guide

fix blip doctest

Italian translation of community.mdx gh-17459

* Change the .view call to .reshape

* Change the .view call to .reshape to all the copies from bart attention

* Fix copies and style

* Fix copies and style

* Fix copies and style

* Fix copies and style

* Fix copies and style

* Revert unneccessary changes

* Revert unneccessary changes

* Revert unneccessary changes

* Revert unneccessary changes

* trying to figure out whether model is NLP

* drop my changes and apply easier fix

* trying to handle all int input types

* fix logic

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

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

* fix reshaping
Fixes #21523

* add test

* styling

* last fixes

* Update src/transformers/models/convbert/modeling_convbert.py

* code quallity

prepare for "__floordiv__ is deprecated  and its behavior will change in a future version of pytorch" (#20211)

* rounding_mode = "floor"  instead of // to prevent behavioral change

* add other TODO

* use `torch_int_div` from pytrch_utils

* same for tests

* fix copies

* style

* use relative imports when needed

* Co-authored-by: sgugger <sylvain.gugger@gmail.com>

* Fix flaky test for log level

* Fix other flaky test

* First commit for the improved PT-TF weight loading

* Remove workarounds from TFEncoderDecoder tests

* Allow a custom weight renaming function in from_pretrained and use that to clean up EncoderDecoder

* make fixup

* First attempt at visionencoderdecoder

* Disable tensorfloat32 in tests to get consistent outputs

* Quick fix to tf_vision_encoder_decoder tests

* make fixup

* Update Blenderbot tests

* Remove unused arg in modeling_tf_opt

* load_tf_sharded_weights had strict=True! This meant transfer learning was impossible, so I'm setting it to False.

* Support prefixes when loading sharded TF checkpoints

* make fixup

* Add test to load sharded models with a weight prefix

* Fix sharded weight loading test

* Add a test for transfer from a sharded checkpoint

* make fixup

* Add test to check that crossloading from PT with a prefix works

* Refactor from_pretrained in the encoderdecoder classes

* Refactor from_pretrained in the encoderdecoder classes

* missmatched -> mismatched

* Explicitly check for None

* No comments showing my very impressive and attractive knowledge of Py3.9+

* Disable TF32 across all TF tests

* Add PipelineTesterMixin

* remove class PipelineTestCaseMeta

* move validate_test_components

* Add for ViT

* Add to SPECIAL_MODULE_TO_TEST_MAP

* style and quality

* Add feature-extraction

* update

* raise instead of skip

* add tiny_model_summary.json

* more explicit

* skip tasks not in mapping

* add availability check

* Add Copyright

* A way to diable irrelevant tests

* update with main

* remove disable_irrelevant_tests

* skip tests

* better skip message

* better skip message

* Add all pipeline task tests

* revert

* Import PipelineTesterMixin

* subclass test classes with PipelineTesterMixin

* Add pipieline_model_mapping

* Fix import after adding pipieline_model_mapping

* Fix style and quality after adding pipieline_model_mapping

* Fix one more import after adding pipieline_model_mapping

* Fix style and quality after adding pipieline_model_mapping

* Fix test issues

* Fix import requirements

* Fix mapping for MobileViTModelTest

* Update

* Better skip message

* pipieline_model_mapping could not be None

* Remove some PipelineTesterMixin

* Fix typo

* revert tests_fetcher.py

* update

* rename

* revert

* Remove PipelineTestCaseMeta from ZeroShotAudioClassificationPipelineTests

* style and quality

* test fetcher for all pipeline/model tests

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

* Add loss for BridgeTowerForMaskedLM and BridgeTowerForImageAndTextRetrieval

* minor fix return_dict

* implement test for loss computation

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Co-authored-by: Tiep Le <97980157+tileintel@users.noreply.github.com>
Co-authored-by: Tiep Le <tiep.le@intel.com>

* fix blip multi gpu

* fix

* final changes

* adapt suggestions

* fix failing slow test

* forward contrib credits from testing and suggestions

* reformat

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

* Use token

* Avoid failure

* better error

* Fix

* fix style

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

* zero shot object detection part 1

* added batch prediction section

* added image guided object detection section

* make style

* added the task guide to the TOC

* minor polishing

* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: Alara Dirik <8944735+alaradirik@users.noreply.github.com>

* added embedded owlvit demo

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

* minor fix

* make style

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Co-authored-by: Steven Liu <59462357+stevhliu@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>

* If applied, this commit fixes generate bug in gptj

* Remove extra same code block

* formatting and test fix

* Conflict fix and declaration error fix

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

* Fix the issue of blip model returning loss even when the label is not provoided

* Fix ruff failure

* Incorporate PR feedbacks

* Incorporate PR feedbacks

* Incorporate PR feedbacks

* Incorporate PR feedbacks

* add v1

* add `Blip2Model`

- add relevant functions
- add tests
- add on automapping

* fix docs

* fix doctest

* fix torchquant issue

* add tests

* fix tf random mask tokens probability

* fix tf random mask tokens probability in collator for langauge modelling

* Fix gradient checkpointing bug in gptneox

* Fix gradient checkpointing bug in modeling_imagegpt.py

* Revert gpt neox changes

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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: saswatmeher <saswatmeher@cse.iitb.ac.in>