Merge branch 'devel'HEADmaster

1 files changed, 83 insertions, 0 deletions

diff --git a/tests/test_neuralNetwork.py b/tests/test_neuralNetwork.py
new file mode 100644
index 0000000..42ba4a1
--- /dev/null
+++ b/tests/test_neuralNetwork.py
@@ -0,0 +1,83 @@
+"""Tests for neural network module."""
+
+import os
+import shutil
+import unittest
+
+from imago.data.enums import DecisionAlgorithms
+from imago.sgfParser.sgf import loadGameTree
+from imago.gameLogic.gameState import GameState
+from imago.engine.keras.neuralNetwork import NeuralNetwork
+from imago.engine.keras.denseNeuralNetwork import DenseNeuralNetwork
+from imago.engine.keras.convNeuralNetwork import ConvNeuralNetwork
+from imago.engine.keras.keras import Keras
+
+class TestNeuralNetwork(unittest.TestCase):
+    """Test neural network module."""
+
+    def testLoadBaseClass(self):
+        """Test error when creating model with the base NeuralNetwork class"""
+
+        self.assertRaises(NotImplementedError,
+                          NeuralNetwork,
+                          "non/existing/file")
+
+    def testNetworks(self):
+        """Test creation of initial model for dense neural network"""
+
+        testModel = 'testModel'
+        testModelPlot = 'testModelPlot'
+
+        games = []
+        for file in [
+                '../collections/minigo/matches/1.sgf',
+                '../collections/minigo/matches/2.sgf',
+                '../collections/minigo/matches/3.sgf'
+                ]:
+            games.append(loadGameTree(file))
+        matches = [game.getMainLineOfPlay() for game in games]
+
+        nn = DenseNeuralNetwork(modelPath=testModel, boardSize=9)
+        nn.trainModel(matches, epochs=1, verbose=0)
+
+        game = GameState(9)
+        nn.pickMove(game.lastMove, game.getCurrentPlayer())
+
+        nn.saveModel(testModel)
+        self.assertTrue(os.path.isdir(testModel))
+        shutil.rmtree(testModel, ignore_errors=True)
+
+        nn.saveModel()
+        self.assertTrue(os.path.isdir(testModel))
+        nn = DenseNeuralNetwork(modelPath=testModel, boardSize=9)
+
+        nn.saveModelPlot(testModelPlot)
+        self.assertTrue(os.path.isfile(testModelPlot))
+
+        shutil.rmtree(testModel, ignore_errors=True)
+        os.remove(testModelPlot)
+
+        nn = ConvNeuralNetwork(testModel, boardSize=9)
+
+    def testKeras(self):
+        """Test keras model loading."""
+
+        gameState = GameState(9)
+        move = gameState.lastMove
+
+        keras = Keras(move)
+        keras.forceNextMove("pass")
+
+        keras = Keras(move, DecisionAlgorithms.DENSE)
+        keras.forceNextMove((3,3))
+
+        keras = Keras(move, DecisionAlgorithms.CONV)
+        self.assertRaises(RuntimeError, keras.forceNextMove, "wrongmove")
+        pickedCoords = keras.pickMove()
+        self.assertTrue(len(pickedCoords) == 2 or pickedCoords == "pass")
+
+        self.assertRaises(RuntimeError, Keras, move, DecisionAlgorithms.MONTECARLO)
+
+
+if __name__ == '__main__':
+    unittest.main()