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@ -35,6 +35,10 @@ bash ./scripts/base-train.sh 0 cifar-10 ResNet110
bash ./scripts/train-nas.sh 0 cifar-10 GDAS_V1 bash ./scripts/train-nas.sh 0 cifar-10 GDAS_V1
bash ./scripts/train-nas.sh 0 cifar-10 GDAS_V2 bash ./scripts/train-nas.sh 0 cifar-10 GDAS_V2
bash ./scripts/train-nas.sh 0 cifar-10 SETN bash ./scripts/train-nas.sh 0 cifar-10 SETN
bash ./scripts/train-nas.sh 0 cifar-10 NASNet
bash ./scripts/train-nas.sh 0 cifar-10 ENASNet
bash ./scripts/train-nas.sh 0 cifar-10 AmoebaNet
bash ./scripts/train-nas.sh 0 cifar-10 PNASNet
bash ./scripts/train-nas.sh 0 cifar-100 SETN bash ./scripts/train-nas.sh 0 cifar-100 SETN
``` ```
The first argument is the GPU-ID to train your program, the second argument is the dataset name, and the last one is the model name. The first argument is the GPU-ID to train your program, the second argument is the dataset name, and the last one is the model name.
@ -80,7 +84,7 @@ If you find that this project helps your research, please consider citing these
@inproceedings{liu2018darts, @inproceedings{liu2018darts,
title = {Darts: Differentiable architecture search}, title = {Darts: Differentiable architecture search},
author = {Liu, Hanxiao and Simonyan, Karen and Yang, Yiming}, author = {Liu, Hanxiao and Simonyan, Karen and Yang, Yiming},
booktitle = {ICLR}, booktitle = {International Conference on Learning Representations (ICLR)},
year = {2018} year = {2018}
} }
@inproceedings{pham2018efficient, @inproceedings{pham2018efficient,
@ -107,31 +111,8 @@ If you find that this project helps your research, please consider citing these
@inproceedings{real2019regularized, @inproceedings{real2019regularized,
title = {Regularized evolution for image classifier architecture search}, title = {Regularized evolution for image classifier architecture search},
author = {Real, Esteban and Aggarwal, Alok and Huang, Yanping and Le, Quoc V}, author = {Real, Esteban and Aggarwal, Alok and Huang, Yanping and Le, Quoc V},
booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence}, booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence (AAAI)},
pages = {4780--4789}, pages = {4780--4789},
year = {2019} year = {2019}
} }
``` ```
```
conda create -n PPD python=3.6 anaconda
pip3 install paddlepaddle-gpu==1.5.1.post97
pip3 install tb-paddle
```
## Active paddlepaddle environment
```
conda activate PPD
bash ./scripts/base-train.sh 0 cifar-10 ResNet110
bash ./scripts/train-nas.sh 0 cifar-10 GDAS_V1
bash ./scripts/train-nas.sh 0 cifar-10 GDAS_V2
bash ./scripts/train-nas.sh 0 cifar-10 SETN
bash ./scripts/train-nas.sh 0 cifar-100 SETN
```
use pytorch training
```
#CUDA_VISIBLE_DEVICES=0 bash ./scripts/com-paddle.sh cifar10 ResNet110 -1
CUDA_VISIBLE_DEVICES=0 bash ./scripts/com-paddle.sh cifar10
```