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AutoDL-Projects/docs/ICLR-2019-DARTS.md

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+# DARTS: Differentiable Architecture Search
+
+DARTS: Differentiable Architecture Search is accepted by ICLR 2019.
+In this paper, Hanxiao proposed a differentiable neural architecture search method, named as DARTS.
+Recently, DARTS becomes very popular due to its simplicity and performance.
+
+## Run DARTS on the NAS-Bench-201 search space
+```
+CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/algos/DARTS-V2.sh cifar10 1 -1
+CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/algos/GDAS.sh     cifar10 1 -1
+```
+
+## Run the first-order DARTS on the NASNet/DARTS search space
+This command will start to use the first-order DARTS to search architectures on the DARTS search space.
+```
+CUDA_VISIBLE_DEVICES=0 bash ./scripts-search/DARTS1V-search-NASNet-space.sh cifar10 -1
+```
+
+After searching, if you want to train the searched architecture found by the above scripts, you need to add the config of that architecture (will be printed in log) in [genotypes.py](https://github.com/D-X-Y/AutoDL-Projects/blob/main/lib/nas_infer_model/DXYs/genotypes.py).
+In future, I will add a more eligent way to train the searched architecture from the DARTS search space.
+
+
+# Citation
+
+```
+@inproceedings{liu2019darts,
+  title     = {{DARTS}: Differentiable architecture search},
+  author    = {Liu, Hanxiao and Simonyan, Karen and Yang, Yiming},
+  booktitle = {International Conference on Learning Representations (ICLR)},
+  year      = {2019}
+}
+```