* create one resolve fn to pull together model defaults + cmd line args
* update attribution comments in some models
* test update train/validation/inference scripts

* All models have 'default_cfgs' dict
* load/resume/pretrained helpers factored out
* pretrained load operates on state_dict based on default_cfg
* test all models in validate
* schedule, optim factor factored out
* test time pool wrapper applied based on default_cfg

Cleanup CheckpointSaver, add support for increasing or decreasing metric, switch to prec1 metric in train loop

Improve creation of data pipeline with prefetch enabled vs disabled, fixup inception_res_v2 and dpn models

Add some Nvidia performance enhancements (prefetch loader, fast collate), and refactor some of training and model fact/transforms