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