Get Weird Structure in Reproducing the Result of GDAS-FRC

Hello . ​Using script NASNet-space-search-by-GDAS-FRC.sh, I got a weird structure as below, which is totally different from cell reported from GDAS Paper(figure 4). The command I use is:

CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/NASNet-space-search-by-GDAS-FRC.sh cifar10 1 -1

Structure in paper: Weird Structure I got:

{'normal': [
    (('skip_connect', 1, 0.1485183) , ('dua_sepc_5x5', 0, 0.13894983)), 
    (('skip_connect', 1, 0.15187271), ('avg_pool_3x3', 1, 0.14358662)), 
    (('skip_connect', 1, 0.14807169), ('max_pool_3x3', 1, 0.14803562)),
    (('max_pool_3x3', 1, 0.15954553), ('skip_connect', 1, 0.14276329))], 
'normal_concat': [2, 3, 4, 5]}

​To find out whether it is only a outlier, I repeat searching procedure several times using different seeds. All result is similar to this weird structure. In these found structures, only one edge containing conv operator and others edges are all ‘skip_connect’ or pooling operator.

MY Environment is :

• NVIDIA-SMI 415.27
• CUDA 10.0
• Python 3.7.7
• cudatoolkit 10.0.130
• cudnn 7.6.5
• Pytorch 1.4.0
• torchvision 0.5.0

[D-X-Y]

{‘normal’: [((‘skip_connect’, 1, 0.15519889), (‘dil_sepc_5x5’, 0, 0.1416643)), ((‘skip_connect’, 1, 0.15950418), (‘max_pool_3x3’, 1, 0.1456287)), ((‘skip_connect’, 1, 0.15625753), (‘max_pool_3x3’, 1, 0.1543942)), ((‘max_pool_3x3’, 1, 0.15630342), (‘skip_connect’, 1, 0.15141682))], ‘normal_concat’: [2, 3, 4, 5]}

Here are my searched results… I also get the same problem. I will try to figure out.

[kadiraltug]

Hello .​Using script NASNet-space-search-by-GDAS-FRC.sh, I got a weird structure as below, which is totally different from cell reported from GDAS Paper(figure 4). The command I use is:

CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/NASNet-space-search-by-GDAS-FRC.sh cifar10 1 -1

Structure in paper: Weird Structure I got:

{'normal': [
    (('skip_connect', 1, 0.1485183) , ('dua_sepc_5x5', 0, 0.13894983)), 
    (('skip_connect', 1, 0.15187271), ('avg_pool_3x3', 1, 0.14358662)), 
    (('skip_connect', 1, 0.14807169), ('max_pool_3x3', 1, 0.14803562)),
    (('max_pool_3x3', 1, 0.15954553), ('skip_connect', 1, 0.14276329))], 
'normal_concat': [2, 3, 4, 5]}

​To find out whether it is only a outlier, I repeat searching procedure several times using different seeds. All result is similar to this weird structure. In these found structures, only one edge containing conv operator and others edges are all ‘skip_connect’ or pooling operator.

MY Environment is :

• NVIDIA-SMI 415.27
• CUDA 10.0
• Python 3.7.7
• cudatoolkit 10.0.130
• cudnn 7.6.5
• Pytorch 1.4.0
• torchvision 0.5.0

How can u use this codes in your code?