ResNet-32 architecture doesn't match ResNet paper

[j201]

The hparams for ResNet-32 seem to define an input layer with 16 filters followed by stacks of layers with 32, 64, and then 128 filters: https://github.com/for-ai/TD/blob/master/hparams/resnet.py#L12

This doesn't match the ResNet paper, which defines ResNet-32 with CIFAR-10 as having an input layer of 16 filters followed by stacks of layers with 16, 32, and 64 filters:

Also, the pruning code reports a total of 1 857 498 parameters, much more than the 0.46M reported in the paper. Changing hps.residual_filters to [16, 16, 32, 64] gives me a much closer value of 468 890 parameters.