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authorInigoGutierrez <inigogf.95@gmail.com>2022-07-01 16:10:15 +0200
committerInigoGutierrez <inigogf.95@gmail.com>2022-07-01 16:10:15 +0200
commitb08408d23186205e71dfc68634021e3236bfb45c (patch)
tree55e5679b6964902dadab1d5737546cfd4f0f2f0a /train.py
parentddde2a9a43daf870c26bef33f47abe45b414c3d0 (diff)
downloadimago-b08408d23186205e71dfc68634021e3236bfb45c.tar.gz
imago-b08408d23186205e71dfc68634021e3236bfb45c.zip
First version.
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+#!/usr/bin/python
+
+"""Starts training a keras neural network."""
+
+import sys
+
+from imago.sgfParser.sgf import loadGameTree
+from imago.engine.keras.denseNeuralNetwork import DenseNeuralNetwork
+from imago.engine.keras.convNeuralNetwork import ConvNeuralNetwork
+
+def main():
+ games = []
+ for file in sys.argv[1:]:
+ print(file)
+ games.append(loadGameTree(file))
+
+ matches = [game.getMainLineOfPlay() for game in games]
+
+ modelFile = ""
+ boardsize = 9
+ nn = DenseNeuralNetwork(modelFile, boardsize)
+ #nn = ConvNeuralNetwork(modelFile, boardsize)
+ nn.trainModel(matches)
+ nn.saveModel()
+
+if __name__ == '__main__':
+ main()