GitLab

* make shufflenet scriptable

* make resnet18 scriptable

* set downsample to identity instead of __constants__ api

* use __constants__ for downsample instead of identity

* import tensor to fix flake

* use torch.Tensor type annotation instead of import

* 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

* add wide resnet

* add docstring for wide resnet

* update WRN-50-2 model

* add docs

* extend WRN docstring

* use pytorch storage for WRN

* fix rebase

* fix typo in docs

Also move weights from ShuffleNet to PyTorch bucket. Additionally, rename shufflenet to make it consistent with the other models

* added progress flag to model getters

* flake8

* bug fix

* backward commpability

* Add dilation option to ResNet

* Add a size check for replace_stride_with_dilation

* Fix ResNeXt model defs with backwards compat for ResNet.

* Fix Python 2.x integer div issue

* Add groups support to ResNet

* Kill BaseResNet

* Make it support multi-machine training

In reference to #729 added comments to clarify the naming and action of the layers performing downsampling in resnets.

* Zero-init the residual branch in resnet

* Add zero_init_residual as an option

* use predefined function

* cleanup resnet

* fix stride

* revert inplanes since it isnt constant

* lint

* AdaptiveAvgpool2d integrated

The Average Pool Layer on SqueezeNet and ResNet was hardcoded, this was changed, now any the input size is accepted.

* error fixed

* linting fixed

nit: replace 4 by expansion

* 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

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

Also add pre-trained ResNet-152 model.

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