GitLab

* [doc] add minimum input size for alexnet builder

* [doc] add minimum input size for vgg builder

* [doc] add minimum input size for squeezenet builder

* [doc] add minimum input size for densenet builder

* [doc] add minimum input size for inception_v3 builder

* [doc] add minimum input size for googlenet builder
Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>

* Fix MNASNet docstrings so they are rendered correctly

* Add dot after url link in models docstrings for consistency

* style: Added annotation typing for vgg

* fix: Fixed annotation typing

* refactor: Removed un-necessary import

* fix: Added missing annotation for kwargs

* fix: Fixed constructor typing

* refactor: Refactored typing to minize changes

* refactor: Refactored typing cast

* fix: Fixed module list typing

* Add docs for video models

* Fix docstrings for resnet and vgg

Fix the old flatten method which use the size(0) to caculate the batch size, the old method will intruduce Gather opertion in the onnx output, which will faild parsed by tensorRT 5.0 (#1134)

* Add paper references to VGG

* Add paper references to ResNet and its variants

* added progress flag to model getters

* flake8

* bug fix

* backward commpability

The update allows VGG to process images larger or smaller than prescribed imagenet size using adaptive average pooling. Will be useful while finetuning or testing on different resolution images. Similar to https://github.com/pytorch/vision/pull/643 and https://github.com/pytorch/vision/pull/672. I did not include adaptive avg pool in features or classifier block so that these predefined blocks can be used as it is.

* cast mnist targer to int

* fix unused variables

* fix syntax in tests

* remove # noqa; rename l variable to line_split; use except OSError

* add W504

* add W504

* add W503,W504 tox.ini

* fix for PyTorch v0.4 (remove .data and add _ for the initializations in nn.init)

* fix m.**.**() style to nn.init.**(**) style

* remove .idea

* fix lines and indents

* fix lines and indents

* change to use `kaming_normal_`

* add `.data` for safety

* add nonlinearity='relu' for sure

* fix indents

Fixes #152

    git ls-files | grep '\.py$' | xargs -n1 -P`nproc` autopep8 -i

* Update VGG doco

Also add pre-trained ResNet-152 model.

  ResNet-152: Prec@1 78.312 Prec@5 94.046