* 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

* Move 'test time pool' to Module that can be used by any model, remove from DPN
* Remove ResNext model file and combine with ResNet
* Remove fbresnet200 as it was an old conversion and pretrained performance not worth param count
* Cleanup adaptive avgmax pooling and add back conctat variant
* Factor out checkpoint load fn

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