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update codes

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D-X-Y
2019-02-01 04:03:35 +11:00
parent 3f9b54d99e
commit 65d9c1c57f
11 changed files with 103 additions and 55 deletions
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4
exps-cnn/train_utils_imagenet.py
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@@ -62,7 +62,7 @@ def main_procedure_imagenet(config, data_path, args, genotype, init_channels, la
total_param, aux_param = count_parameters_in_MB(basemodel), count_parameters_in_MB(basemodel.auxiliary_param())
print_log('Network =>\n{:}'.format(basemodel), log)
#print_FLOPs(basemodel, (1,3,224,224), [print_log, log])
print_FLOPs(basemodel, (1,3,224,224), [print_log, log])
print_log('Parameters : {:} - {:} = {:.3f} MB'.format(total_param, aux_param, total_param - aux_param), log)
print_log('config : {:}'.format(config), log)
print_log('genotype : {:}'.format(genotype), log)
@@ -75,7 +75,7 @@ def main_procedure_imagenet(config, data_path, args, genotype, init_channels, la
criterion_smooth = CrossEntropyLabelSmooth(class_num, config.label_smooth).cuda()
optimizer = torch.optim.SGD(model.parameters(), config.LR, momentum=config.momentum, weight_decay=config.decay, nestero=True)
optimizer = torch.optim.SGD(model.parameters(), config.LR, momentum=config.momentum, weight_decay=config.decay, nesterov=True)
if config.type == 'cosine':
scheduler = torch.optim.lr_scheduler.CosineAnnealingLR(optimizer, float(config.epochs))
elif config.type == 'steplr':