Submit

This section explains how to submit your solution. It includes three parts:

1. Neural Networks

2. Code Packaging

3. Solution Files

1. Neural Networks

If your method involves training (e.g., RL agent), please include:

• model.py: model definition

• train.py: training script

• inference.py: inference script

• checkpoints/: folder with model weights (e.g., best_model.pth)

Example command:

python inference.py --checkpoint checkpoints/best_model.pth --input rlsolver/data/gset_14.txt --output rlsolver/result/gset_14.txt

2. Code Packaging

Please include:

• Python source files (.py)

• requirements.txt with all dependencies

• A brief README.md with install and run instructions

3. Solution Files

Your output can be saved inside the rlsolver/result/ folder.

Each line represents the assignment of a node to one of two sets (for MaxCut):

1 2
2 1
3 2
4 1
5 2

• The first number is the node ID (starting from 1)

• The second number is the assigned set (1 or 2)

This format directly follows the example in the README. Make sure to include all nodes and follow the naming exactly.