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update CVPR-2019-GDAS re-train NASNet-search-space searched models

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D-X-Y
2020-03-06 19:29:07 +11:00
parent 8b6df42f1f
commit 9a83814a46
17 changed files with 278 additions and 21 deletions
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16
lib/nas_infer_model/__init__.py
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@@ -6,12 +6,22 @@
# Currently, this package is used to reproduce the results in GDAS (Searching for A Robust Neural Architecture in Four GPU Hours, CVPR 2019).
##################################################
import torch
import os, torch
def obtain_nas_infer_model(config):
def obtain_nas_infer_model(config, extra_model_path=None):
if config.arch == 'dxys':
from .DXYs import CifarNet, ImageNet, Networks
genotype = Networks[config.genotype]
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':