<strong>Highlight</strong>: we equip one-shot NAS with an architecture sampler and train network weights using uniformly sampling.
One-Shot Neural Architecture Search via Self-Evaluated Template Network is accepted by ICCV 2019.
## Requirements and Preparation
Please install `Python>=3.6` and `PyTorch>=1.2.0`.
### Usefull tools
1. Compute the number of parameters and FLOPs of a model:
```
from utils import get_model_infos
flop, param = get_model_infos(net, (1,3,32,32))
```
2. Different NAS-searched architectures are defined [here](https://github.com/D-X-Y/AutoDL-Projects/blob/master/lib/nas_infer_model/DXYs/genotypes.py).
## Usage
Please use the following scripts to train the searched SETN-searched CNN on CIFAR-10, CIFAR-100, and ImageNet.