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Using python2 style '/' will convert int type to float in python3 which will cause the following error when creating FloatTensor:

TypeError: torch.FloatTensor constructor received an invalid combination of arguments - got (float, int, int, int), but expected one of:
 * no arguments
 * (int ...)
      didn't match because some of the arguments have invalid types: (float, int, int, int)

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

* Add SqueezeNet 1.0 and 1.1 models
* Selectively avoid inplace in SqueezeNet
* Use Glorot uniform initialization in SqueezeNet
* Make all ReLU in SqueezeNet in-place
* Add pretrained SqueezeNet 1.0 and 1.1
* Minor fixes in SqueezeNet models

* Update VGG doco

Also add pre-trained ResNet-152 model.

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