New Datasets
* Add Caltech101, Caltech256, and CelebA (775)
* ImageNet dataset (764) (858) (870)
* Added Semantic Boundaries Dataset (808) (865)
* Add VisionDataset as a base class for all datasets (749) (859) (838) (876) (878)
New Models
Classification
* Add GoogLeNet (Inception v1) (678) (821) (828) (816)
* Add MobileNet V2 (818) (917)
* Add ShuffleNet v2 (849) (886) (889) (892) (916)
* Add ResNeXt-50 32x4d and ResNeXt-101 32x8d (822) (852) (917)
Segmentation
* Fully-Convolutional Network (FCN) with ResNet 101 backbone
* DeepLabV3 with ResNet 101 backbone
Detection
* Faster R-CNN R-50 FPN trained on COCO train2017 (898) (921)
* Mask R-CNN R-50 FPN trained on COCO train2017 (898) (921)
* Keypoint R-CNN R-50 FPN trained on COCO train2017 (898) (921) (922)
Breaking changes
* Make `CocoDataset` ids deterministically ordered (868)
New Transforms
* Add bias vector to `LinearTransformation` (793) (843) (881)
* Add Random Perspective transform (781) (879)
Bugfixes
* Fix user warning when applying `normalize` (810)
* Fix logic error in `check_integrity` (871)
Improvements
* Fixing mutation of 2d tensors in `to_pil_image` (762)
* Replace `tensor.view` with `tensor.unsqueeze(0)` in `make_grid` (765)
* Change usage of `view` to `reshape` in `resnet` to enable running with mkldnn (890)
* Improve `normalize` to work with tensors located on any device (787)
* Raise an `IndexError` for `FakeData.__getitem__()` if the index would be out of range (780)
* Aspect ratio is now sampled from a logarithmic distribution in `RandomResizedCrop`. (799)
* Modernize inception v3 weight initialization code (824)
* Remove duplicate code from densenet load_state_dict (827)
* Replace `endswith` calls in a loop with a single `endswith` call in `DatasetFolder` (832)
* Added missing dot in webp image extensions (836)
* fix inconsistent behavior for `~` expression (850)
* Minor Compressions in statements in `folder.py` (874)
* Minor fix to evaluation formula of `PILLOW_VERSION` in `transforms.functional.affine` (895)
* added `is_valid_file` parameter to `DatasetFolder` (867)
* Add support for joint transformations in `VisionDataset` (872)
* Auto calculating return dimension of `squeezenet` forward method (884)
* Added `progress` flag to model getters (875) (910)
* Add support for other normalizations (i.e., `GroupNorm`) in `ResNet` (813)
* Add dilation option to `ResNet` (866)
Testing
* Add basic model testing. (811)
* Add test for `num_class` in `test_model.py` (815)
* Added test for `normalize` functionality in `make_grid` function. (840)
* Added downloaded directory not empty check in `test_datasets_utils` (844)
* Added test for `save_image` in utils (847)
* Added tests for `check_md5` and `check_integrity` (873)
Misc
* Remove shebang in `setup.py` (773)
* configurable version and package names (842)
* More hub models (851)
* Update travis to use more recent GCC (891)
Documentation
* Add comments regarding downsampling layers of resnet (794)
* Remove unnecessary bullet point in InceptionV3 doc (814)
* Fix `crop` and `resized_crop` docs in `functional.py` (817)
* Added dimensions in the comments of googlenet (788)
* Update transform doc with random offset of padding due to `pad_if_needed` (791)
* Added the argument `transform_input` in docs of InceptionV3 (789)
* Update documentation for MNIST datasets (778)
* Fixed typo in `normalize()` function. (823)
* Fix typo in squeezenet (841)
* Fix typo in DenseNet comment (857)
* Typo and syntax fixes to transform docstrings (887)