add configs for the searched shape (NeurIPS19)

This commit is contained in:
D-X-Y 2019-12-07 21:39:46 +11:00
parent d175a361bd
commit 2ad81707f8
5 changed files with 53 additions and 0 deletions

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@ -57,6 +57,9 @@ CUDA_VISIBLE_DEVICES=0,1 bash ./scripts-search/search-cifar.sh cifar10 ResNet56
args: `cifar10` indicates the dataset name, `ResNet56` indicates the basemodel name, `CIFARX` indicates the searching hyper-parameters, `0.47/0.57` indicates the expected FLOP ratio, `-1` indicates the random seed.
### Model Configuration
The searched shapes for ResNet-20/32/56/110/164 in Table 3 in the original paper are listed in [`configs/NeurIPS-2019`](https://github.com/D-X-Y/NAS-Projects/tree/master/configs/NeurIPS-2019).
## [One-Shot Neural Architecture Search via Self-Evaluated Template Network](https://arxiv.org/abs/1910.05733)

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{
"dataset" : ["str" , "cifar"],
"arch" : ["str" , "resnet"],
"depth" : ["int" , "20"],
"module" : ["str" , "ResNetBasicblock"],
"super_type" : ["str" , "infer-shape"],
"zero_init_residual" : ["bool" , "0"],
"class_num" : ["int" , "10"],
"search_mode" : ["str" , "shape"],
"xchannels" : ["int" , ["3", "16", "6", "4", "4", "4", "4", "4", "32", "32", "12", "19", "32", "28", "64", "64", "64", "64", "64", "44"]],
"xblocks" : ["int" , ["3", "3", "3"]],
"estimated_FLOP" : ["float" , "22.444472"]
}

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{
"dataset" : ["str" , "cifar"],
"arch" : ["str" , "resnet"],
"depth" : ["int" , "32"],
"module" : ["str" , "ResNetBasicblock"],
"super_type" : ["str" , "infer-shape"],
"zero_init_residual" : ["bool" , "0"],
"class_num" : ["int" , "10"],
"search_mode" : ["str" , "shape"],
"xchannels" : ["int" , ["3", "16", "6", "4", "12", "4", "4", "16", "9", "9", "6", "14", "32", "32", "9", "19", "28", "9", "32", "19", "32", "9", "64", "64", "64", "64", "64", "64", "64", "32", "38", "32"]],
"xblocks" : ["int" , ["5", "5", "5"]],
"estimated_FLOP" : ["float" , "34.945344"]
}

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{
"dataset" : ["str" , "cifar"],
"arch" : ["str" , "resnet"],
"depth" : ["int" , "20"],
"module" : ["str" , "ResNetBasicblock"],
"super_type" : ["str" , "infer-shape"],
"zero_init_residual" : ["bool" , "0"],
"class_num" : ["int" , "100"],
"search_mode" : ["str" , "shape"],
"xchannels" : ["int" , ["3", "16", "4", "4", "4", "4", "6", "4", "32", "32", "9", "19", "32", "28", "64", "64", "64", "64", "64", "64"]],
"xblocks" : ["int" , ["3", "3", "3"]],
"estimated_FLOP" : ["float" , "22.433792"]
}

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{
"dataset" : ["str" , "cifar"],
"arch" : ["str" , "resnet"],
"depth" : ["int" , "32"],
"module" : ["str" , "ResNetBasicblock"],
"super_type" : ["str" , "infer"],
"zero_init_residual" : ["bool" , "0"],
"class_num" : ["int" , "100"],
"xchannels" : ["int" , ["3", "16", "4", "4", "4", "14", "6", "4", "8", "4", "4", "4", "32", "32", "9", "28", "28", "28", "28", "28", "32", "32", "64", "64", "64", "64", "64", "64", "64", "64", "64", "64"]],
"estimated_FLOP" : ["float" , "42.493184"]
}