iicd/autodl-projects
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

update NAS-Bench

Browse Source
This commit is contained in:
D-X-Y
2020-03-09 19:38:00 +11:00
parent 9a83814a46
commit e59eb804cb
35 changed files with 693 additions and 64 deletions
Download Patch File Download Diff File Expand all files Collapse all files

4
docs/CVPR-2019-GDAS.md
View File

@@ -39,10 +39,10 @@ If you are interested in the configs of each NAS-searched architecture, they are
### Searching on the NASNet search space
Please use the following scripts to use GDAS to search as in the original paper:
```
CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/GDAS-search-NASNet-space.sh cifar10 1 -1
CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/NASNet-space-search-by-GDAS.sh cifar10 1 -1
```
**After searching***, if you want to re-train the searched architecture found by the above script, you can use the following script:
**After searching**, if you want to re-train the searched architecture found by the above script, you can use the following script:
```
CUDA_VISIBLE_DEVICES=0 bash ./scripts/retrain-searched-net.sh cifar10 gdas-searched \
output/search-cell-darts/GDAS-cifar10-BN1/checkpoint/seed-945-basic.pth 96 -1

7
docs/ICCV-2019-SETN.md
View File

@@ -30,6 +30,13 @@ CUDA_VISIBLE_DEVICES=0 bash ./scripts/nas-infer-train.sh cifar100 SETN 96 -1
CUDA_VISIBLE_DEVICES=0,1,2,3 bash ./scripts/nas-infer-train.sh imagenet-1k SETN 256 -1
```
### Searching on the NASNet search space
Please use the following scripts to use SETN to search as in the original paper:
```
CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/NASNet-space-search-by-SETN.sh cifar10 1 -1
```
### Searching on the NAS-Bench-201 search space
The searching codes of SETN on a small search space (NAS-Bench-201).
```
CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/algos/SETN.sh cifar10 1 -1

4
docs/NAS-Bench-201.md
View File

@@ -146,6 +146,10 @@ api.get_more_info(112, 'cifar10', None, False, True)
api.get_more_info(112, 'ImageNet16-120', None, False, True) # the info of last training epoch for 112-th architecture (use 200-epoch-hyper-parameter and randomly select a trial)
```
Please use the following script to show the best architectures on each dataset:
```show the best architecture
python exps/NAS-Bench-201/show-best.py
```
## Instruction to Re-Generate NAS-Bench-201