GitLab

* setting 100 seeds, let's see if it fails

* Passed with 100, so setting 10

* adding multiweight support for deeplabv3 prototype models

* adding default values for optional params

* fixing bug

* addressing PR comment

* Change test_random_apply

* Change test_random_choice

* Change test_randomness

* took care of RandomVert/HorizFlip

* take care of RandomGrayScale

* minor cleanup

* avoid 0 degree rotation just in case

* Fix flakiness on the TestStochasticDepth test.

* Fix minor bug when p=1.0

* Remove device and dtype setting.

* cache dataset info

* try loading categories file by default
Co-authored-by: Francisco Massa <fvsmassa@gmail.com>

* Adding multi-weight support to LRASPP

* Adding tests for segmentation models.

* Skip segmentation test by default.

Relocate fails to find nvjpeg unless its present in the library search path.

* Refactoring tests.

* Fixing lint.

* Skip tests for models that don't have weights.

Co-authored-by: Prabhat Roy <prabhatroy@fb.com>

* replace np.frombuffer with torch.frombuffer in MNIST prototype

* cleanup

* appease mypy

* more cleanup

* clarify inplace offset

* fix num bytes for floating point data

Summary:
Pull Request resolved: https://github.com/pytorch/vision/pull/4718



As title

Reviewed By: hanton

Differential Revision: D31853335

fbshipit-source-id: 7e8afb7280bbdf81418dfbdfc329ab49837ea42e
Co-authored-by: Yuchen Huang <hyc@fb.com>

Summary:
Pull Request resolved: https://github.com/pytorch/vision/pull/4620

Pull Request resolved: https://github.com/pytorch/nestedtensor/pull/455



Fixes missing kernel guards as identified by D30072495

Reviewed By: jingsh, xush6528

Differential Revision: D31553158

fbshipit-source-id: 80de017ba2ddc52e2a684df9b3eae5de84ed49f4
Co-authored-by: Richard Barnes <rbarnes@fb.com>

Summary:
Pull Request resolved: https://github.com/pytorch/vision/pull/4571



Fixing windows build for `torchvision` when `MOBILE` is defined. In `csrc/vision.cpp`, since `PyMODINIT_FUNC` depends on `Python.h` I added the same condition for `PyMODINIT_FUNC` as the one for `import <PyTorch.h>`.

Reviewed By: malfet

Differential Revision: D31488734

fbshipit-source-id: fd52a9ab161288d9c8bf3b9e0ab9da856a4ebadb
Co-authored-by: Mengwei Liu <larryliu@fb.com>

* fix cuda installation failure in packaging

* rm stop windows upgrade

* Update cuda_install.bat
Co-authored-by: Nikita Shulga <nshulga@fb.com>

* Removed unnecessary if from setup.py

* Removed empty line

* Update model checkpoint for resnet50.

* Add get_weight method to retrieve weights from name.

* Update the references to support prototype weights.

* Fixing mypy typing.

* Switching to a python 3.6 supported equivalent.

* Add unit-test.

* Add optional num_classes.

Summary: As titled.

Reviewed By: sallysyw

Differential Revision: D31813675

fbshipit-source-id: 8ff879be172530bcc41aae5d71c67e1e90f09cbf
Co-authored-by: Kai Zhang <kaizh@fb.com>

* Expand usage logging to detection models

Summary: Track all detection model instantiation.

Reviewed By: sallysyw

Differential Revision: D31741603

fbshipit-source-id: 89467db5d89ea41c5a9ab95d1846264d0a1f4199

* Fix lint
Co-authored-by: Kai Zhang <kaizh@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>

* Add mutli-weight support for FCN.

* Rename base_size to resize_size.

* Add type to default argument

To resolve issue #4694

* Resolve issue #4694

Add missing types on argument parser

* Update with ufmt

formatted with ufmt

* Updated with review

Updated with review

* Update type of arguments

Add train.py from video_classification, similarity and train_quantization.py
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Adding multiweight support for mnasnet prototype

* Adressing PR comments

* adding return type to _mnasnet
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

GPU tests have special step to install the driver, CUDA install step shouldl just install the runtime
never

Fixes regression introduced by https://github.com/pytorch/vision/pull/4421

* Adding multiweight support for mobilenetv3 prototype

* 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.

* 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>

* adding interpolation model information to all classification prototype models

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

* Migrate mnist dataset from np.frombuffer

* Add a copy with bytearray for non-writable buffers

* Add byte reversal for mnist
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* make mypy more strict for prototype datasets

* fix code format

* apply strictness only to datasets

* fix more mypy issues

* cleanup

* fix mnist annotations

* refactor celeba

* warn on redundant casts

* remove redundant cast

* simplify annotation

* fix import

* WIP

* cleaner code

* Add tests

* Add docs

* Assert dtype

* put back check

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

* add prototype imagenet dataset

* add missing checksums

* fix mypy

* add human readable categories

* cleanup

* sort categories ascending based on wnid

* remove accidentally added file

* cleanup category file generation

* fix mypy

* fix category file inclusion

* fix deprecated import

* Move TorchVision conda package to use pytorch-mutex

This is follow up after https://github.com/pytorch/builder/pull/823

 that gets rids of `feature` and migrate it to `run_constrained`

* Update packaging/torchvision/meta.yaml
Co-authored-by: Eli Uriegas <1700823+seemethere@users.noreply.github.com>

* Update packaging/torchvision/meta.yaml
Co-authored-by: Eli Uriegas <1700823+seemethere@users.noreply.github.com>
Co-authored-by: Eli Uriegas <1700823+seemethere@users.noreply.github.com>