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how to build the route training input from the routes #19

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opened 2025-10-14 17:08:14 -06:00 by navan · 0 comments
navan commented 2025-10-14 17:08:14 -06:00
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Originally created by @eacwecwecd on 1/11/2021

Hi binghong

I am currently confused about building AI inputs from the routes like

['Cc1ccc(C(=O)N2CCC(c3ccc(-c4cnn(C)c4)cc3)CC2)cc1NC(=O)c1ccc(NC(C)C)nc1>>Cc1ccc(C(=O)N2CCC(c3ccc(-c4cnn(C)c4)cc3)CC2)cc1NC(=O)c1ccc(Cl)nc1.CC(C)N', 'Cc1ccc(C(=O)N2CCC(c3ccc(-c4cnn(C)c4)cc3)CC2)cc1NC(=O)c1ccc(Cl)nc1>>O=C(Cl)c1ccc(Cl)nc1.Cc1ccc(C(=O)N2CCC(c3ccc(-c4cnn(C)c4)cc3)CC2)cc1N', 'Cc1ccc(C(=O)N2CCC(c3ccc(-c4cnn(C)c4)cc3)CC2)cc1N>>Cn1cc(-c2ccc(C3CCNCC3)cc2)cn1.Cc1ccc(C(=O)O)cc1N'].

I had a look at the code at the trainer.py and the .pt data file, the training input was fps, values, r_costs, t_values, r_fps, r_masks from the training routes data. Could you share the information (code better) about how can I buld the the AI input from the routes data.

*Originally created by @eacwecwecd on 1/11/2021* Hi binghong I am currently confused about building AI inputs from the routes like ['Cc1ccc(C(=O)N2CCC(c3ccc(-c4cnn(C)c4)cc3)CC2)cc1NC(=O)c1ccc(NC(C)C)nc1>>Cc1ccc(C(=O)N2CCC(c3ccc(-c4cnn(C)c4)cc3)CC2)cc1NC(=O)c1ccc(Cl)nc1.CC(C)N', 'Cc1ccc(C(=O)N2CCC(c3ccc(-c4cnn(C)c4)cc3)CC2)cc1NC(=O)c1ccc(Cl)nc1>>O=C(Cl)c1ccc(Cl)nc1.Cc1ccc(C(=O)N2CCC(c3ccc(-c4cnn(C)c4)cc3)CC2)cc1N', 'Cc1ccc(C(=O)N2CCC(c3ccc(-c4cnn(C)c4)cc3)CC2)cc1N>>Cn1cc(-c2ccc(C3CCNCC3)cc2)cn1.Cc1ccc(C(=O)O)cc1N']. I had a look at the code at the trainer.py and the .pt data file, the training input was fps, values, r_costs, t_values, r_fps, r_masks from the training routes data. Could you share the information (code better) about how can I buld the the AI input from the routes data.
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Reference: github/retro_star#19
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