* Align implementation with reference implementation used by paper.

ResNet-18 with preactivation as by https://github.com/kuangliu/pytorch-cifar is using ResNet with preactivation block with 2 consecutive convolution layers in the block. Existing implementation was using 3.

Weight decay was set incorrectly.

Architecture aligned with main repository approach: defined functions for bottleneck and regular PreActResNet blocks

Support for multiple depths added.

* PreActivation block: no BnRelu should appear outside of the residual branch

* Code migration clean up: blocks reareanged, variable names aligned

* Correct reference implementation: BnRelu is used in identity branch only before a convolutional layer.

* Updated model accuracies after sigle run

* Documentation update

* closer to mixup experiment settings

* fix lint