GitLab

* Adding FLOPs and size to model metadata

* Adding weight size to quantization models

* Small refactor of rich metadata

* Removing unused code

* Fixing wrong entries

* Adding .DS_Store to gitignore

* Renaming _flops to _ops

* Adding number of operations to quantization models

* Reflecting _flops change to _ops

* Renamed ops and weight size in individual model doc pages

* Linter fixes

* Rounding ops to first decimal

* Rounding num ops and sizes to 3 decimals

* Change naming of columns.

* Update tables
Co-authored-by: Toni Blaslov <tblaslov@fb.com>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Model registration mechanism.

* Add overwrite options to the dataset prototype registration mechanism.

* Adding example models.

* Fix module filtering

* Fix linter

* Fix docs

* Make name optional if same as model builder

* Apply updates from code-review.

* fix minor bug

* Adding getter for model weight enum

* Support both strings and callables on get_model_weight.

* linter fixes

* Fixing mypy.

* Renaming `get_model_weight` to `get_model_weights`

* Registering all classification models.

* Registering all video models.

* Registering all detection models.

* Registering all optical flow models.

* Fixing mypy.

* Registering all segmentation models.

* Registering all quantization models.

* Fixing linter

* Registering all prototype depth perception models.

* Adding tests and updating existing tests.

* Fix linters

* Fix tests.

* Add beta annotation on docs.

* Fix tests.

* Apply changes from code-review.

* Adding documentation.

* Fix docs.

* upgrade usort to

* Also update black

* Actually use 1.0.2

* Apply pre-commit
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Classif models

* Detection

* Segmentation

* quantization

* Video

* optical flow

* tests

* Fix docs

* Fix Video dataset

* Consistency for RAFT dataset names

* use ImageNet-1K

* Use COCO-val2017-VOC-labels for segmentation

* formatting

* Improving the auto-gen doc.

* Adding details for AlexNet, ConvNext, DenseNet, EfficientNets, GoogLeNet and InceptionV3.

* Fixing location of `_docs`

* Adding docs in the remaining classification models.

* Fix linter

* Reinstate and deprecate `model_urls` and `quant_model_urls`

* Apply suggestions from code review
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Move todo location

* Add alexnet

* Add densenet

* Add efficientnet

* Add googlenet.

* Add inception.

* Add mobilenetv3

* Add regnet

* Add resnet

* Add shufflenetv2

* Fix linter

* Add squeezenet

* Add vgg

* Add vit

* Add quantized googlenet

* Add quantized inceptionv3

* Add quantized mobilenet_v3

* Add quantized resnet

* Add quantized shufflenetv2

* Fix incorrect imports

* Add faster_rcnn

* Add fcos

* Add keypoint rcnn

* Add mask rcnn

* Add retinanet

* Add ssd

* Add ssdlite

* Add deeplabv3

* Add fcn

* Add lraspp.

* Add video resnet

* Removing weights for shufflenetv2_x1.5 and shufflenetv2_x2.0

* Update the comments
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* [FEAT] Add efficientnetv2 doc.

* [FIX] Precommits fix.

* Apply suggestions from code review
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* [DOC] Add new EfficientNet doc.

* [DOC] Add missing file.

* [FIX] Precommits fix.

* [FIX] Precommits fix.

* [ENH] Integrate few documentation comments from code review

* Update docs/source/models/efficientnet.rst
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Restructuring metrics meta-data for detection, segmentation and optical flow.

* Renaming acc to pixel_acc for segmentation

* Restructure video meta-data.

* Restructure classification and quantization meta-data.

* Fix tests.

* Fix documentation

* Removing `task`, `architecture` and `quantization`

* Fix mypy

* Remove size field

* Remove unused import.

* Fix mypy

* Remove size from schema list.

* update todo

* Simplify with assert

* Adding min_size to all models.

* Update RAFT min size to 128

* Remove publication_year and interpolation meta

* Add type to _COMMON_META and _COMMON_SWAG_META to prevent error from mypy check

* Remove test to check interpolation and publication_year meta
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>

* Extend the EfficientNet class to support v1 and v2.

* Refactor config/builder methods and add prototype builders

* Refactoring weight info.

* Update dropouts based on TF config ref

* Update BN eps on TF base_config

* Use Conv2dNormActivation.

* Adding pre-trained weights for EfficientNetV2-s

* Add Medium and Large weights

* Update stats with single batch run.

* Add accuracies in the docs.

* Add ops.conv3d

* Refactor for conv2d and 3d

* Refactor

* Fix bug

* Addres review

* Fix bug

* nit fix

* Fix flake

* Final fix

* remove documentation

* fix linter

* Update all the implementations to use new Conv

* Small doc fix
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Joao Gomes <jdsgomes@fb.com>

* Consolidating __repr__ strings
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* log API v3

* make torchscript happy

* make torchscript happy

* add missing logs to constructor

* log ops C++ API as well

* fix type hint

* check function with isinstance
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* revamp log api usage method

Co-authored-by: Nicolas Hug <nicolashug@fb.com>

Summary: We would like to track the internal usage of TorchVision components. We're tracking [datasets usage](https://fburl.com/daiquery/dqpmemn3

) now. This diff expand the tracking to all models.

Reviewed By: fmassa

Differential Revision: D31441632

fbshipit-source-id: e26072e582ac9f832c2056307ebf0eccf2ed6c9c
Co-authored-by: Kai Zhang <kaizh@fb.com>

* adding efficientnet to prototype

* Removing _efficientnet_conf from prototype and main efficientnet classification models

* fixing merge conflicts

* fixing merge conflicts

* fixing lint errors

* fixing lint errors

* fixing lint errors

* adding efficientnet to prototype

* renaming _efficientnet_model in torchvision.model to be aligned with prototype implementation

* adding specific cop sizes to ech model

* adding specific cop and resize transforms

* fixing lint errors

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

* rename pretrained model versions
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* rename pretrained model versions
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* rename pretrained model versions
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* rename pretrained model versions
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* rename pretrained model versions
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* rename pretrained model versions
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* rename pretrained model versions
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* rename pretrained model versions
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* adressing PR comments
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* 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>

* Moving _make_divisible to utils.

* Replace the old ConvBNReLU and ConvBNActivation layers

* Fix minor bug.

* Moving SE layer to ops.

* Adding deprecation warnings on old layers.

* Apply changes to regnets.

* allow custom activation in SqueezeExcitation

* use ReLU as the default activation

* make scale activation parameterizable
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* 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.