##################################################### # Copyright (c) Xuanyi Dong [GitHub D-X-Y], 2019.01 # ##################################################### # I write this package to make AutoDL-Projects to be compatible with the old GDAS projects. # Ideally, this package will be merged into lib/models/cell_infers in future. # Currently, this package is used to reproduce the results in GDAS (Searching for A Robust Neural Architecture in Four GPU Hours, CVPR 2019). ################################################## import os, torch def obtain_nas_infer_model(config, extra_model_path=None): if config.arch == 'dxys': from .DXYs import CifarNet, ImageNet, Networks from .DXYs import build_genotype_from_dict if config.genotype is None: if extra_model_path is not None and not os.path.isfile(extra_model_path): raise ValueError('When genotype in confiig is None, extra_model_path must be set as a path instead of {:}'.format(extra_model_path)) xdata = torch.load(extra_model_path) current_epoch = xdata['epoch'] genotype_dict = xdata['genotypes'][current_epoch-1] genotype = build_genotype_from_dict(genotype_dict) else: genotype = Networks[config.genotype] if config.dataset == 'cifar': return CifarNet(config.ichannel, config.layers, config.stem_multi, config.auxiliary, genotype, config.class_num) elif config.dataset == 'imagenet': return ImageNet(config.ichannel, config.layers, config.auxiliary, genotype, config.class_num) else: raise ValueError('invalid dataset : {:}'.format(config.dataset)) else: raise ValueError('invalid nas arch type : {:}'.format(config.arch))