6 Commits (76539d905e08f1f0c88752f83845193faa936ed1)

Author	SHA1	Message	Date
Ross Wightman	76539d905e	Some transform/data/loader refactoring, hopefully didn't break things ... * factor out data related constants to own file * move data related config helpers to own file * add a variant of RandomResizeCrop that randomizes interpolation method * remove old Numpy version of RandomErasing * cleanup torch version of RandomErasing and use it in either GPU loader batch mode or single image cpu Transform	5 years ago
Ross Wightman	0a853990e7	Add distributed sampler that maintains order of original dataset (for validation)	6 years ago
Ross Wightman	71afec86d3	Loader tweaks	6 years ago
Ross Wightman	0562b91c38	Add per model crop pct, interpolation defaults, tie it all together ... * create one resolve fn to pull together model defaults + cmd line args * update attribution comments in some models * test update train/validation/inference scripts	6 years ago
Ross Wightman	c328b155e9	Random erasing crash fix and args pass through	6 years ago
Ross Wightman	9c3859fb9c	Uniform pretrained model handling. ... * 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	6 years ago