GitLab

Co-authored-by: Nicolas Hug <nh.nicolas.hug@gmail.com>

Co-authored-by: Philip Meier <github.pmeier@posteo.de>

Co-authored-by: Philip Meier <github.pmeier@posteo.de>

Co-authored-by: Max Chuprov <m.chuprov@expasoft.tech>

Co-authored-by: Philip Meier <github.pmeier@posteo.de>

* Fixing inverted center_crop check on Classification preset

* Remove the `--train-center-crop` flag.

* Added maxvit architecture and tests

* rebased + addresed comments

* Revert "rebased + addresed comments"

This reverts commit c5b28398cd48d2f3403c7c8eeefbaba9df05fcfe.

* Re-added model changes after revert

* aligned with partial original implementation

* removed submitit script fixed lint

* mypy fix for too many arguments

* updated old tests

* removed per batch lr scheduler and seed setting

* removed ontap

* added docs, validated weights

* fixed test expect, moved shape assertions in the begging for torch.fx compatibility

* mypy fix

* lint fix

* added legacy interface

* added weight link

* updated docs

* Update references/classification/train.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Update torchvision/models/maxvit.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* adressed comments

* update ra_maginuted and augmix_severity default values

* adressed some comments

* remove input_channels parameter
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Moving basefiles outside of prototype and porting Alexnet, ConvNext, Densenet and EfficientNet.

* Porting googlenet

* Porting inception

* Porting mnasnet

* Porting mobilenetv2

* Porting mobilenetv3

* Porting regnet

* Porting resnet

* Porting shufflenetv2

* Porting squeezenet

* Porting vgg

* Porting vit

* Fix docstrings

* Fixing imports

* Adding missing import

* Fix mobilenet imports

* Fix tests

* Fix prototype tests

* Exclude get_weight from models on test

* Fix init files

* Porting googlenet

* Porting inception

* porting mobilenetv2

* porting mobilenetv3

* porting resnet

* porting shufflenetv2

* Fix test and linter

* Fixing docs.

* Porting Detection models (#5617)

* fix inits

* fix docs

* Port faster_rcnn

* Port fcos

* Port keypoint_rcnn

* Port mask_rcnn

* Port retinanet

* Port ssd

* Port ssdlite

* Fix linter

* Fixing tests

* Fixing tests

* Fixing vgg test

* Porting Optical Flow, Segmentation, Video models (#5619)

* Porting raft

* Porting video resnet

* Porting deeplabv3

* Porting fcn and lraspp

* Fixing the tests and linter

* Porting docs, examples, tutorials and galleries (#5620)

* Fix examples, tutorials and gallery

* Update gallery/plot_optical_flow.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Fix import

* Revert hardcoded normalization

* fix uncommitted changes

* Fix bug

* Fix more bugs

* Making resize optional for segmentation

* Fixing preset

* Fix mypy

* Fixing documentation strings

* Fix flake8

* minor refactoring
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Resolve conflict

* Porting model tests (#5622)

* Porting tests

* Remove unnecessary variable

* Fix linter

* Move prototype to extended tests

* Fix download models job

* Update CI on Multiweight branch to use the new weight download approach (#5628)

* port Pad to prototype transforms (#5621)

* port Pad to prototype transforms

* use literal

* Bump up LibTorchvision version number for Podspec to release Cocoapods (#5624)
Co-authored-by: Anton Thomma <anton@pri.co.nz>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* pre-download model weights in CI docs build (#5625)

* pre-download model weights in CI docs build

* move changes into template

* change docs image

* Regenerated config.yml
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Anton Thomma <11010310+thommaa@users.noreply.github.com>
Co-authored-by: Anton Thomma <anton@pri.co.nz>

* Porting reference scripts and updating presets (#5629)

* Making _preset.py classes

* Remove support of targets on presets.

* Rewriting the video preset

* Adding tests to check that the bundled transforms are JIT scriptable

* Rename all presets from *Eval to *Inference

* Minor refactoring

* Remove --prototype and --pretrained from reference scripts

* remove  pretained_backbone refs

* Corrections and simplifications

* Fixing bug

* Fixing linter

* Fix flake8

* restore documentation example

* minor fixes

* fix optical flow missing param

* Fixing commands

* Adding weights_backbone support in detection and segmentation

* Updating the commands for InceptionV3

* Setting `weights_backbone` to its fully BC value (#5653)

* Replace default `weights_backbone=None` with its BC values.

* Fixing tests

* Fix linter

* Update docs.

* Update preprocessing on reference scripts.

* Change qat/ptq to their full values.

* Refactoring preprocessing

* Fix video preset

* No initialization on VGG if pretrained

* Fix warning messages for backbone utils.

* Adding star to all preset constructors.

* Fix mypy.
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Anton Thomma <11010310+thommaa@users.noreply.github.com>
Co-authored-by: Anton Thomma <anton@pri.co.nz>

* Adding basic augmix implementation.

* Finish the implementation.

* Add tests and documentation.

* Fix tests.

* Simplify code.

* Speed optimizations.

* Per image weights instead of per batch.

* Fix tests.

* Update torchvision/transforms/autoaugment.py
Co-authored-by: vfdev <vfdev.5@gmail.com>

* Changing the default severity value to get by default the same strength as RandAugment.
Co-authored-by: vfdev <vfdev.5@gmail.com>

* Update EMA every X iters.

* Adding AdamW optimizer.

* Adjusting EMA decay scheme.

* Support custom weight decay for Normalization layers.

* Fix identation bug.

* Change EMA adjustment.

* Quality of life changes to faciliate testing

* ufmt format

* Fixing imports.

* Adding FixRes improvement.

* Support EMA in store_model_weights.

* Adding interpolation values.

* Change train_crop_size.

* Add interpolation option.

* Removing hardcoded interpolation and sizes from the scripts.

* Fixing linter.

* Incorporating feedback from code review.

* add ufmt as code formatter

* cleanup

* quote ufmt requirement

* split imports into more groups

* regenerate circleci config

* fix CI

* clarify local testing utils section

* use ufmt pre-commit hook

* split relative imports into local category

* Revert "split relative imports into local category"

This reverts commit f2e224cde2008c56c9347c1f69746d39065cdd51.

* pin black and usort dependencies

* fix local test utils detection

* fix ufmt rev

* add reference utils to local category

* fix usort config

* remove custom categories sorting

* Run pre-commit without fixing flake8

* got a double import in merge
Co-authored-by: Nicolas Hug <nicolashug@fb.com>

* Replaced ToTensor with a combination of PILToTensor and ConvertImageDtype

* Pass dtype

* Initial Proposal

* Tensor Save Test + Test Name Fix

* Formatting + removing unused argument

* fix old argument

* fix isnan check error + indexing error with jit

* Fix Flake8 error.

* Fix MyPy error.

* Fix Flake8 error.

* Fix PyTorch JIT error in UnitTests due to type annotation.

* Fixing tests.

* Removing type ignore.

* Adding support of ta_wide in references.

* Move methods in classes.

* Moving new classes to the bottom.

* Specialize to TA to TAwide

* Add missing type

* Fixing lint

* Fix doc

* Fix search space of TrivialAugment.
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Vasilis Vryniotis <vvryniotis@fb.com>

* Adding randaugment implementation

* Refactoring.

* Adding num_magnitude_bins.

* Adding FIXME.

* Adding code skeleton

* Adding MBConvConfig.

* Extend SqueezeExcitation to support custom min_value and activation.

* Implement MBConv.

* Replace stochastic_depth with operator.

* Adding the rest of the EfficientNet implementation

* Update torchvision/models/efficientnet.py

* Replacing 1st activation of SE with SiLU.

* Adding efficientnet_b3.

* Replace mobilenetv3 assets with custom.

* Switch to standard sigmoid and reconfiguring BN.

* Reconfiguration of efficientnet.

* Add repr

* Add weights.

* Update weights.

* Adding B5-B7 weights.

* Update docs and hubconf.

* Fix doc link.

* Fix typo on comment.

* Adding presets in the classification reference scripts.

* Adding presets in the object detection reference scripts.

* Adding presets in the segmentation reference scripts.

* Adding presets in the video classification reference scripts.

* Moving flip at the end to align with image classification signature.