REST

REST is a reinforcement learning framework for rectilinear Steiner minimum tree (RSMT) construction. Read our paper for more details:

• Jinwei Liu, Gengjie Chen, and Evangeline FY Young. "REST: Constructing Rectilinear Steiner Minimum Tree via Reinforcement Learning." 2021 58th ACM/IEEE Design Automation Conference (DAC). IEEE, 2021.

Dependencies

• Python 3.6+
• PyTorch 1.10.0+
• GeoSteiner 5.1 (included)

Training

Start a new training process for degree 20 by

python3 train.py --degree 20

Testing

1. Test the trained model using randomly generated data set by

python3 test.py --degree 20

2. Or use the trained parameters included with this repository

python3 test.py --degree 20 --experiment DAC21

3. As mentioned in the paper, the percentage error can be further reduced by using multiple transformations of the input point set for inference. Inference using all eight transformations by

python3 test.py --degree 20 --experiment DAC21 --transformation 8

4. Lastly, if you want to test the same data set as in the paper

python3 test.py --degree 20 --test_data test_set/test20.txt

Results

Using only one of the transformations for inference

Using all eight transformations for inference

License

READ THIS LICENSE AGREEMENT CAREFULLY BEFORE USING THIS PRODUCT. BY USING THIS PRODUCT YOU INDICATE YOUR ACCEPTANCE OF THE TERMS OF THE FOLLOWING AGREEMENT. THESE TERMS APPLY TO YOU AND ANY SUBSEQUENT LICENSEE OF THIS PRODUCT.

License Agreement for REST

Copyright (c) 2022, The Chinese University of Hong Kong All rights reserved.

CU-SD LICENSE (adapted from the original BSD license) Redistribution of the any code, with or without modification, are permitted provided that the conditions below are met.

1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.

2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.

3. Neither the name nor trademark of the copyright holder or the author may be used to endorse or promote products derived from this software without specific prior written permission.

4. Users are entirely responsible, to the exclusion of the author, for compliance with (a) regulations set by owners or administrators of employed equipment, (b) licensing terms of any other software, and (c) local, national, and international regulations regarding use, including those regarding import, export, and use of encryption software.

THIS FREE SOFTWARE IS PROVIDED BY THE AUTHOR "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR OR ANY CONTRIBUTOR BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, EFFECTS OF UNAUTHORIZED OR MALICIOUS NETWORK ACCESS; PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.