GitLab

* Initial commit

* Just a copy of modeling_idefics.py that will be ported to TF

* - Prepend TF to the name of all classes
- Convert pytorch ops to TF (not all operations are converted yet)

* Add TF imports

* Add autotranslated files

* Add TF classes to model_tf_auto.py

* Add the TF classes in model_doc

* include auto-translated code

* Adopted from auto-translated version

* Add a forgotten super().build

* Add test code for TF version.

* Fix indentation and load pytorch weights for now

* Some fixes. Many tests are still failing but some are passing now.

- I have added TODO's for some of the hacks I made to unblock me
  and I will address them soon
- I have the processing_idefics.py hacked in my view to support TF temporarily

* Add ALL_LAYERNORM_LAYERS to match pytorch

* Revert "Add ALL_LAYERNORM_LAYERS to match pytorch"

This reverts commit 7e0a35119b4d7a6284d04d8c543fba1b29e573c9 as it
is not needed in the tf implementation.

* Fix freeze_relevant_params()

* Some more fixes

* Fix test_attention_outputs

* Add tf stuff to processing_idefics.py

processing_idefics.py supports both pytorch and tf now.

test_processor_idefics.py for pytorch is passing, so i didn't break anything
but still some issues with tf. I also need to add tf tests in
test_processor_idefics.py.

* Pass return_tensors to image processing code and fix test

* Pass return_tensors to the image processor __init__

* Fix several test cases

- Make input to some of the forward pass of type `TFModelInputType`
- Decorate main layer forward pass with `@unpack_inputs`
- Decorate main layer with `@keras_serializable`
- Pass `inputs` to TFIdeficsModel

* Some more fixes forgotten in last commit

* Fix processing code and vision_tf.py

* Fix perceiver bug

* Import from

* Auto-add build() methods + style pass

* Fix build() errors due to `None` being passed as shape to some layers

* Change name in TFIdeficsForVisionText2Text to attribute in IdeficsForVisionText2Text

* Fix pytorch weights load for tf2

There were a lot of `name=` missing in weight initialization code.

* Attempt to fix CI

* Add back accidently removed line

* Remove torch-specific stuff from the TF test file

* make fix-copies, make style, remove autotranslated files

* Fixes to imports/docstrings

* Let's try the from future import in desperation

* Fix the core random_attention_mask fn to match the torch/flax behaviour

* Clean random_attention_mask up correctly

* Remove torch-only test

* Fix loss shape, couple of nits

* make style

* Don't test for OOB embeddings because IDEFICS uses those deliberately

* Fix loss computation to handle masking

* Fix test failures when flattening

* Fix some test failures

- Add cross attention gate which was missing and wasn't being passed arround
- Fix overwriting of image_attention_mask due to hack I had for dummy inputs

* Add a proper stateless scaled_dot_product_attention

* make style

* Adding missing attribute from the PyTorch version

* Small cleanups to decoupledlinearlayer in case that helps

* Pass epsilon to LayerNormalization

* Attemp to fix pytorch weight cross-loading for TFIdeficsEmbedding

* Fix a bug in TFIdeficsGatedCrossAttentionLayer

* Patching up build() methods

* Constant self.inv_freq

* Constant self.inv_freq

* First working version

The TF implementation works now, there was a bug in the TFIdeficsDecoupledLinear
where the weights were mis-intialized (in_features,out_features)
when it should be: (out_features, in_features)

I have tested this so far with tiny-random and idefics-9b-instruct
and gives correct output.

I also dumped the final outputs for both pytorch and TF
and they are identical.

* Fix some test failures

* remove print statement

* Fix return_tensors

* Fix CI test failure check_code_quality

* Attempt to fix CI failures by running `make fixup`

The hardcoded IDs in test_modeling_tf_idefics.py are for the integration
test and makes that file unreadable and should probably be moved to a seperate file.

* Attempt to fix tests_pr_documentation_tests

* Fix a test failure in test_image_processing_idefics.py

* Fix test test_pt_tf_model_equivalence

* Fix a few failures

* Tiny fix

* Some minor fixes

* Remove a duplicate test

* Override a few test failures for IDEFICS

- `test_keras_save_load` is passing now
- `test_compile_tf_model` is still failing

* Fix processing_idefics.py after rebase

* Guard import keras with is_tf_available

* fix check code quality

* fix check code quality

* Minor fixes

* Skip test_save_load temporarily

This test passed on my local box but fails on the CI, skipping
for now to see if there are other remaining failures on the CI.

* Run `ruff format tests src utils`

* Fix last failing test, `test_compile_tf_model`

* Add fixes for vision_tf.py

I forgot to add this file in last commit.

* Minor fixes

* Replace "<<<" with "<<" for doc tests

IDEFICS-9B is too big for doctest runner, so don't run it there

* Make code more readable

* Fix bug after code review

I added a layer_norm_eps to IdeficsConfig but I don't even need it
since the vision config has a layer_norm_eps.

* Fix after code review

Use original code tokenizer.convert_tokens_to_ids

* Keep PyTorch as the default return_tensors

* Fixes to modeling_tf after code review

* Fixes from code review

- Remove all references of `TF_IDEFICS_PRETRAINED_MODEL_ARCHIVE_LIST`
- Pass 1e-5 to LayerNormalization in perceiver

* Run ruff

* Undo a change

* Refactor processing code after Matt's suggestion

* Remove TODO's that aren't needed anymore

* For pytorch, Use original pytorch processing code from main

Since this PR is a TF port it shouldn't make any modifications
to pytorch IDEFICS code. This changes undo's the pytorch processing
modifications I made and uses original code from main.

* Update tests/models/idefics/test_modeling_idefics.py

* Update tests/models/idefics/test_modeling_tf_idefics.py

* Add missing imports for is_pt_tf_cross_test

* [DO NOT MERGE]: This is a commit for debugging and will be reverted

The cross test `test_pt_tf_model_equivalence` passes locally but
fails when running on the CI. This commit is to help debug that
and will be reverted.

* Revert "[DO NOT MERGE]: This is a commit for debugging and will be reverted"

This reverts commit 8f0d709ec5bd46685fb0b4259d914ffee794875b.

* [DO NOT MERGE]: This commit is for debugging a CI failure and will be reverted

* [DO NOT MERGE]: This commit is for debugging a CI failure and will be reverted

* Revert "[DO NOT MERGE]: This commit is for debugging a CI failure and will be reverted"

This reverts commit 998cc38b8c3d313bf5e5eb55a7f5b7b881897b89.

* Revert "[DO NOT MERGE]: This commit is for debugging a CI failure and will be reverted"

This reverts commit 1c695ac4219c4ae4d39b330b01744dc27deb7dd4.

* Don't skip test_save_load

IIRC test_save_load was also failing on the CI but not on my local
box, it might be easier to debug that on the CI first than the cross tests

* Debugging commit, will be reverted

* Revert "Debugging commit, will be reverted"

This reverts commit 8eafc8e41e20c4e95a3a90834f06a6e9f445e2d5.

* Override `test_save_load` and push model to save

Maybe this will help me repro this weird bug

* pass my repo_id

* add endpoint

* Pass a temp (write) token just for this CI

* Undo last few commits, still pushing to hub for model debugging

The issue seems to be with save_pretrained(),  when I looked at the model saved
from the CI test failure it is basically empty and has no weights.
`self.save_weights(..)` seems to be failing in save_pretrained but needs
more debugging

* Add logging to modeling tf utils, will be reverted just for debugging

* Debugging, will revert

* Revert "Debugging, will revert"

This reverts commit 9d0d3075fb7c82d8cde3a5c76bc8f3876c5c55d3.

* Revert "Add logging to modeling tf utils, will be reverted just for debugging"

This reverts commit 774b6b7b1c17b3ce5d7634ade768f2f686cee617.

* Remove `test_save_load`

The CI failures are gone after my latest rebase, no idea why
but I was still saving the model to my hub on HF and the tf_model.h5
file now has everything.

* Run make fix-copies

* Run ruff format tests src utils

* Debugging commit, will be reverted

* Run ruff, also trigger CI run

* Run ruff again

* Undo debugging commit

---------
Co-authored-by: Matt <rocketknight1@gmail.com>
Co-authored-by: Matt <Rocketknight1@users.noreply.github.com>

* rename

* restore

* mappings

* unedited tests+docs

* docs

* fixes

* fix auto-sync breakage

* cleanup

* wip

* wip

* add fetch_images

* remove einops dependency

* update

* fix

* fix

* fix

* fix

* fix

* re-add

* add batching

* rework

* fix

* improve

* add Leo as I am extending his work

* cleanup

* fix

* cleanup

* slow-test

* fix

* fix

* fixes

* deal with warning

* rename modified llama classes

* rework fetch_images

* alternative implementation

* cleanup

* strict version

* cleanup

* [`IDEFICS`] Fix idefics ci (#25056)

* Fix IDEFICS CI

* fix test file

* fixup

* some changes to make tests pass

* fix

* fixup

* Update src/transformers/models/idefics/configuration_idefics.py
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

---------
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* remove compat checks

* style

* explain that Idefics is not for training from scratch

* require pt>=2.0

* fix idefics vision config (#25092)

* fix idefics vision config

* fixup

* clean

* Update src/transformers/models/idefics/configuration_idefics.py

---------
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* cleanup

* style

* cleanup

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

* upcase

* sequence of images

* handle the case with no images

* Update src/transformers/image_processing_utils.py
Co-authored-by: Victor SANH <victorsanh@gmail.com>

* support pure lm take 2

* support tokenizer options

* parameterize num_channels

* fix upcase

* s|IdeficsForCausalLM|IdeficsForVisionText2Text|g

* manual to one line

* addressing review

* unbreak

* remove clip dependency

* fix test

* consistency

* PIL import

* Idefics prefix

* Idefics prefix

* hack to make tests work

* style

* fix

* fix

* revert

* try/finally

* cleanup

* clean up

* move

* [`IDEFICS`] Fix idefics config refactor (#25149)

* refactor config

* nuke init weights

* more refactor

* oops

* remove visual question answering pipeline support

* Update src/transformers/models/idefics/clip.py
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>

* Update src/transformers/models/idefics/modeling_idefics.py

* cleanup

* mv clip.py vision.py

* tidyup

---------
Co-authored-by: Stas Bekman <stas00@users.noreply.github.com>
Co-authored-by: Stas Bekman <stas@stason.org>

* fix

* license

* condition on pt

* fix

* style

* fix

* rm torchvision dependency, allow custom transforms

* address review

* rework device arg

* add_eos_token

* s/transforms/transform/

* fix top level imports

* fix return value

* cleanup

* cleanup

* fix

* style

* license

* license

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

* add a wrapper to freeze vision layears

* tidyup

* use the correct std/mean settings

* parameterize values from config

* add tests/models/idefics/test_image_processing_idefics.py

* add test_processor_idefics.py

* cleanup

* cleanups

* fix

* fix

* move to the right group

* style

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

* add perceiver config

* reset

* missing arg docs

* Apply suggestions from code review
Co-authored-by: Leo Tronchon <leo.tronchon@gmail.com>

* address review comments

* inject automatic end of utterance tokens (#25218)

* inject automatic end of utterance tokens

* fix

* fix

* fix

* rework to not use the config

* not end_of_utterance_token at the end

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

* address review

* Apply suggestions from code review
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>

* Update src/transformers/image_processing_utils.py
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>

* [`Idefics`] add image_embeddings option in generate-related methods (#25442)

* add image_embeddings option in generate-related methods

* style

* rename image_embeddings and allow perceiver embeddings precomputation

* compute embeddings within generate

* make is_encoder_decoder= True the default in config

* nested if else fix

* better triple check

* switch if elif order for pixel values / img embeds

* update model_kwargs perceiver only at the end

* use _prepare_model_inputs instead of encoder_decoder logic

* fix comment typo

* fix config default for is_encoder_decoder

* style

* add typehints

* precompute in forward

* doc builder

* style

* pop instead of get image hidden states

* Trigger CI

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

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

* fix * + indentation + style

* simplify a bit the use_resampler logic using comments

* update diocstrings

* Trigger CI

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

* fix rebase changes

* unbreak #25237 - to be fixed in follow up PRs

* is_composition = False

* no longer needed

---------
Co-authored-by: leot13 <leo.tronchon@gmail.com>
Co-authored-by: Younes Belkada <49240599+younesbelkada@users.noreply.github.com>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
Co-authored-by: Victor SANH <victorsanh@gmail.com>
Co-authored-by: Joao Gante <joaofranciscocardosogante@gmail.com>
Co-authored-by: Nicolas Patry <patry.nicolas@protonmail.com>
Co-authored-by: Arthur <48595927+ArthurZucker@users.noreply.github.com>

* Refactor image processor test mixin

- Move test_call_numpy, test_call_pytorch, test_call_pil to mixin
- Rename mixin to reflect handling of logic more than saving
- Add prepare_image_inputs, expected_image_outputs for tests

* Fix for oneformer

* Removal of deprecated methods and specify versions

* Fix tests

* Result of black 23.1

* Update target to Python 3.7

* Switch flake8 to ruff

* Configure isort

* Configure isort

* Apply isort with line limit

* Put the right black version

* adapt black in check copies

* Fix copies

* Update imports and test fetcher

* Revert but keep test fetcher update

* Fix imports

* Fix all imports

* Replace fe with ip names

* Add generate kwargs to `AutomaticSpeechRecognitionPipeline` (#20952)

* Add generate kwargs to AutomaticSpeechRecognitionPipeline

* Add test for generation kwargs

* Update image processor parameters if creating with kwargs (#20866)

* Update parameters if creating with kwargs

* Shallow copy to prevent mutating input

* Pass all args in constructor dict - warnings in init

* Fix typo

* Rename tester class

* Rebase and tidy up

* Fixup

* Use ImageProcessingSavingTestMixin

* Update property ref in tests

* Update property ref in tests

* Update recently merged in models

* Small fix
Co-authored-by: bofeng huang <bofenghuang7@gmail.com>

* Add test_image_processing_common.py

* Fix typo

* Update imports and test fetcher

* Revert but keep test fetcher update

* Fix imports

* Fix all imports

* Formatting fix

* Update tests/test_image_processing_common.py

* Rename files

* Update file names in tests

* Update parameters if creating with kwargs

* Shallow copy to prevent mutating input

* Pass all args in constructor dict - warnings in init

* Fix typo

* 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>

* move test model folders (TODO: fix imports and others)

* fix (potentially partially) imports (in model test modules)

* fix (potentially partially) imports (in tokenization test modules)

* fix (potentially partially) imports (in feature extraction test modules)

* fix import utils.test_modeling_tf_core

* fix path ../fixtures/

* fix imports about generation.test_generation_flax_utils

* fix more imports

* fix fixture path

* fix get_test_dir

* update module_to_test_file

* fix get_tests_dir from wrong transformers.utils

* update config.yml (CircleCI)

* fix style

* remove missing imports

* update new model script

* update check_repo

* update SPECIAL_MODULE_TO_TEST_MAP

* fix style

* add __init__

* update self-scheduled

* fix add_new_model scripts

* check one way to get location back

* python setup.py build install

* fix import in test auto

* update self-scheduled.yml

* update slack notification script

* Add comments about artifact names

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

* Split file_utils in several submodules

* Fixes

* Add back more objects

* More fixes

* Who exactly decided to import that from there?

* Second suggestion to code with code review

* Revert wront move

* Fix imports

* Adapt all imports

* Adapt all imports everywhere

* Revert this import, will fix in a separate commit

* Per-folder tests reorganization
Co-authored-by: sgugger <sylvain.gugger@gmail.com>
Co-authored-by: Stas Bekman <stas@stason.org>

* First commit

* Add conversion script

* Make conversion script work for base model

* More improvements

* Update conversion script, works for vqa

* Add indexing argument to meshgrid

* Make conversion script work for ViltForPreTraining

* Add ViltForPreTraining to docs

* Fix device issue

* Add processor

* Add MinMaxResize to feature extractor

* Implement call method of ViltProcessor

* Fix tests

* Add integration test

* Add loss calculation for VQA

* Improve tests

* Improve some more tests

* Debug tests

* Small improvements

* Add support for attention_mask

* Remove mask_it

* Add pixel_mask

* Add tests for ViltFeatureExtractor

* Improve tests

* Add ViltForNaturalLanguageVisualReasoning

* Add ViltForNaturalLanguageVisualReasoning to conversion script

* Minor fixes

* Add support for image_embeds, update docstrings to markdown

* Update docs to markdown

* Improve conversion script

* Rename ViltForPreTraining to ViltForMaskedLM

* Improve conversion script

* Convert docstrings to markdown

* Fix code example of retrieval model

* Properly convert masked language model

* Add integration test for nlvr

* Fix code quality

* Apply suggestions from code review

* Add copied from statements

* Fix pretrained_config_archive_map

* Fix docs

* Add model to README

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

* Apply more suggestions from code review

* Make code more readable

* Add ViltForNaturalLanguageVisualReasoning to the tests

* Rename ViltForVisualQuestionAnswering to ViltForQuestionAnswering

* Replace pixel_values_2 by single tensor

* Add hidden_states and attentions

* Fix one more test

* Fix all tests

* Update year

* Fix rebase issues

* Fix another rebase issue

* Remove ViltForPreTraining from auto mapping

* Rename ViltForImageRetrievalTextRetrieval to ViltForImageAndTextRetrieval

* Make it possible to use BertTokenizerFast in the processor

* Use BertTokenizerFast by default

* Rename ViltForNaturalLanguageVisualReasoning, define custom model output
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Rename target to labels in DetrFeatureExtractor

* Update DetrFeatureExtractor tests accordingly

* Improve docs of DetrFeatureExtractor

* Improve docs

* Make style

* Squash all commits of modeling_detr_v7 branch into one

* Improve docs

* Fix tests

* Style

* Improve docs some more and fix most tests

* Fix slow tests of ViT, DeiT and DETR

* Improve replacement of batch norm

* Restructure timm backbone forward

* Make DetrForSegmentation support any timm backbone

* Fix name of output

* Address most comments by @LysandreJik

* Give better names for variables

* Conditional imports + timm in setup.py

* Address additional comments by @sgugger

* Make style, add require_timm and require_vision to testsé

* Remove train_backbone attribute of DetrConfig, add methods to freeze/unfreeze backbone

* Add png files to fixtures

* Fix type hint

* Add timm to workflows

* Add `BatchNorm2d` to the weight initialization

* Fix retain_grad test

* Replace model checkpoints by Facebook namespace

* Fix name of checkpoint in test

* Add user-friendly message when scipy is not available

* Address most comments by @patrickvonplaten

* Remove return_intermediate_layers attribute of DetrConfig and simplify Joiner

* Better initialization

* Scipy is necessary to get sklearn metrics

* Rename TimmBackbone to DetrTimmConvEncoder and rename DetrJoiner to DetrConvModel

* Make style

* Improve docs and add 2 community notebooks
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>