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

Support GDAS (FRC), see details in docs/CVPR-2019-GDAS.md

Browse Source
This commit is contained in:
D-X-Y
2020-08-18 00:50:33 +00:00
parent 75eefa3d44
commit ffd23a6cbd
7 changed files with 212 additions and 17 deletions
Download Patch File Download Diff File Expand all files Collapse all files

7
docs/CVPR-2019-GDAS.md
View File

@@ -37,9 +37,14 @@ CUDA_VISIBLE_DEVICES=0,1,2,3 bash ./scripts/nas-infer-train.sh imagenet-1k GDAS_
If you are interested in the configs of each NAS-searched architecture, they are defined at [genotypes.py](https://github.com/D-X-Y/AutoDL-Projects/blob/master/lib/nas_infer_model/DXYs/genotypes.py).
### Searching on the NASNet search space
Please use the following scripts to use GDAS to search as in the original paper:
```
# search for both normal and reduction cells
CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/NASNet-space-search-by-GDAS.sh cifar10 1 -1
# search for the normal cell while use a fixed reduction cell
CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/NASNet-space-search-by-GDAS-FRC.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:
@@ -52,7 +57,9 @@ Note that `gdas-searched` is a string to indicate the name of the saved dir and
The above script does not apply heavy augmentation to train the model, so the accuracy will be lower than the original paper.
If you want to change the default hyper-parameter for re-training, please have a look at `./scripts/retrain-searched-net.sh` and `configs/archs/NAS-*-none.config`.
### Searching on a small search space (NAS-Bench-201)
The GDAS searching codes on a small search space:
```
CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/algos/GDAS.sh cifar10 1 -1