pytorch-image-models/data/__init__.py

from data.dataset import Dataset
from data.transforms import *
from data.loader import create_loader
from data.random_erasing import RandomErasingTorch, RandomErasingNumpy
Add some Nvidia performance enhancements (prefetch loader, fast collate), and refactor some of training and model fact/transforms 2019-03-10 14:23:16 -07:00			`from data.dataset import Dataset`
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 2019-04-11 21:32:16 -07:00			`from data.transforms import *`
			`from data.loader import create_loader`
Add some Nvidia performance enhancements (prefetch loader, fast collate), and refactor some of training and model fact/transforms 2019-03-10 14:23:16 -07:00			`from data.random_erasing import RandomErasingTorch, RandomErasingNumpy`