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ZhangZiYang11 / tensorflow-implement-of-Learning-Combinatorial-Optimization-Algorithms-over-Graphs

tensorflow implement of Learning Combinatorial Optimization Algorithms over Graphs
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Thank you for your code #1

Open Dicer98k opened 5 months ago

Dicer98k commented 5 months ago

Hi, thank you very much for providing the code. I'd like to ask on what hardware configuration this model was trained, how long it took to train, and if I want to run this code, how should I adjust the parameters to minimize the running time as much as possible?

ZhangZiYang11 commented 5 months ago

Hi, I trained this model with MX350 and CUDA10.0. It took less than 10000 steps to get acceptable approximation ratio. I would suggest to use model trained on small graphs as pre-training, which is controlled by the "pre_training" parameter., and it will restore model form path "'/tmp/saved_models/'+pre_training". Also, it will cost a lot of time to generate optimal solutions with CPLEX when number of nodes is very huge. You can generate graphs and optimal solutions before training (this should change "mvc_env.py", in which graphs and optimal solutions are generated).

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Dicer98k commented 5 months ago

I see ~. I am currently modifying your code to implement my problem. In my problem, the feature length of the nodes is 4. Therefore, I have added another dimension [4] to the relevant parameters of the Q function. Currently, I have some issues about the values ​​of 'obs'. If you don't mind, can we exchange WeChat contacts? I would like to consult and discuss some issues with you. If it's okay, I'll send you my WeChat ID to your BUAA email.

ZhangZiYang11 commented 5 months ago

I see ~. I am currently modifying your code to implement my problem. In my problem, the feature length of the nodes is 4. Therefore, I have added another dimension [4] to the relevant parameters of the Q function. Currently, I have some issues about the values ​​of 'obs'. If you don't mind, can we exchange WeChat contacts? I would like to consult and discuss some issues with you. If it's okay, I'll send you my WeChat ID to your BUAA email.

Sure, you can add my WeChat directly: 'zzy15839625479'