GitLab

* Add deprecation warnings on vision::models

* Change the C++ example.

* Chage readme.

* Update deprecation warning.

* Fix training resuming in references/segmentation

* Clarification for training resnext101_32x8d

* Update references/classification/README.md
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* Added Exponential Moving Average support to classification reference script

* Addressed review comments

* Updated model argument

* Added paper references to detection models

* Ignore linter warning

* Break long line into two

Co-authored-by: Vassilis Nicodemou <nikodim@ics.forth.gr>
Co-authored-by: Philip Meier <github.pmeier@posteo.de>

Summary:
Pull Request resolved: https://github.com/pytorch/pytorch/pull/63414



Misuse of raw pointer in here where stack is never nullable.
ghstack-source-id: 136938318

Reviewed By: ejguan

Differential Revision: D30375410

fbshipit-source-id: 9d65b620bb76d90d886c800f54308520095d58ee
Co-authored-by: Zhengxu Chen <zhxchen17@fb.com>

* add fx feature extraction util

* Make it possible to use train and eval mode

* FX feature extraction - Tweaks and small bug fixes

* FX feature extraction - add tests

* move to feature_extraction.py, add LeafModuleAwareTracer, add docs

* Tweaks to docs

* addressing latest round of feedback

* undo line spacing changes

* change type hints in docstrings

* fix sphinx indentation

* expose feature_extraction

* add maskrcnn example

* add api refernce subheading

* address latest review notes, refactor names, fix regex, cosmetics

* Add back efficientnet to models

* fix tests for effnet

* fix linting issue

* fix test tracer kwargs
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* Add types in transform.

* Trace on eval mode.
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* WIP on fixing index overflow issue

* Fixed backward pass for large num_kernels

* Fixed clang formatting

* Fixed GET_BLOCKS int/int64_t types issue
Co-authored-by: vfdev-5 <vfdev-5@gmail.com>
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* Fix RA bugs.

* Fix bins for TA.

* 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>

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

* Adding docs for RandAugment.

* Fix docs.

* Adding randaugment implementation

* Refactoring.

* Adding num_magnitude_bins.

* Adding FIXME.

* Adding label smoothing on classification reference.

* Replace underscore with dash.

* Explicitely store a distance value that is reused 

I don't see a reason to calculate the value twice for each distance. 

Knowing that this code is going to be called at every epoch and that probably there is not a compiler that optimizes this (+ also code clarity), I think is best to store the value for x and y.

* Update torchvision/models/detection/_utils.py
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>

* removing spaces
Co-authored-by: Nicolas Hug <contact@nicolas-hug.com>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Fixed a couple of typos and removed unnecessary bracket

* Fixed clang error

* fix

* add typings

* fixup some more types

* Type more

* remove mypy ignore

* add missing typings

* fix a few mypy errors

* fix mypy errors

* fix mypy

* ignore types

* fixup annotation

* fix remaining types

* cleanup #TODO comments
Co-authored-by: Philip Meier <github.pmeier@posteo.de>
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* style: Added typing annotations

* Specified types for iter and seek.
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
Co-authored-by: Vasilis Vryniotis <vvryniotis@fb.com>

* Update UCF101 docstring

* addressing @NicolasHugs comments

* Fixed flake8 error
Co-authored-by: Prabhat Roy <prabhatroy@fb.com>

[ghstack-poisoned]
Co-authored-by: Bert Maher <bertrand@fb.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.

[FBcode->GH] Port quantize_val and dequantize_val into torchvision to avoid at::native and android xplat incompatibility (#4311)

Summary:
This diff ports `quantize_val` and `dequantize_val` from at::native to torchvision because native kernels are incompatible with android xplat builds (see D30234056).

This should only be temporary until we find a way to move those functions out of at::native, or until the at::native / android incompatibility disappears.

Reviewed By: fmassa

Differential Revision: D30393619

fbshipit-source-id: 18b7b1b349ad9a24088a120e23da7535f7fa7ddc
Co-authored-by: Nicolas Hug <nicolashug@fb.com>