9 Commits (b32361c9f8e0ad7ba99670e562ff07dabc43c397)

Author	SHA1	Message	Date
Ross Wightman	4bb5e9b224	Ported Tensorflow pretrained EfficientNet weights and some model cleanup ... * B0-B3 weights ported from TF with close to paper accuracy * Renamed gen_mobilenet to gen_efficientnet since scaling params go well beyond 'mobile' specific * Add Tensorflow preprocessing option for closer images to source repo	6 years ago
Ross Wightman	4d2056722a	Mixup and prefetcher improvements ... * Do mixup in custom collate fn if prefetcher enabled, reduces performance impact * Move mixup code to own file * Add arg to disable prefetcher * Fix no cuda transfer when prefetcher off * Random erasing when prefetcher off wasn't changed to match new args, fixed * Default random erasing to off (prob = 0.) for train	6 years ago
Ross Wightman	780c0a96a4	Change args for RandomErasing so only one required for pixel/color mode	6 years ago
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	6 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