debug for unit test

tianshou/core/mcts/unit_test/ZOGame.py

@@ -29,17 +29,10 @@ class ZOTree:
         length = len(seq)
         if length != self.depth:
             raise ValueError("The game is not terminated!")
-        ones = 0
+	result = np.sum(seq)
-        zeros = 0
+        if result > self.size:
-        for i in range(len(seq)):
-            if seq[i] == 0:
-                zeros += 1
-            if seq[i] == 1:
-                ones += 1
-        result = ones - zeros
-        if result > 0:
             winner = 1
-        elif result < 0:
+        elif result < self.size:
             winner = -1
         else:
             winner = 0
@@ -98,7 +91,7 @@ class ZOTree:
 if __name__ == "__main__":
     size = 2
     game = ZOTree(size)
-    seq = [1, -1, 1, 1]
+    seq = [1, 0, 1, 1]
     result = game.executor_do_move([seq, 1], 1)
     print(result)
     print(seq)

tianshou/core/mcts/unit_test/agent.py

@@ -17,7 +17,7 @@ class Agent:
     def gen_move(self, seq):
         if len(seq) >= 2 * self.size:
             raise ValueError("Game is terminated.")
-        mcts = MCTS(self.simulator, self.evaluator, [seq, self.color], 2)
+        mcts = MCTS(self.simulator, self.evaluator, [seq, self.color], 2, inverse=True)
         mcts.search(max_step=50)
         N = mcts.root.N
         N = np.power(N, 1.0 / temp)

tianshou/core/mcts/unit_test/game.py

@@ -6,7 +6,7 @@ if __name__ == '__main__':
     print("Our game has 2 players.")
     print("Player 1 has color 1 and plays first. Player 2 has color -1 and plays following player 1.")
     print("Both player choose 1 or 0 for an action.")
-    size = 1
+    size = 2
     print("This game has {} iterations".format(size))
     print("If the final sequence has more 1 that 0, player 1 wins.")
     print("If the final sequence has less 1 that 0, player 2 wins.")

tianshou/core/mcts/unit_test/mcts.py

@@ -187,7 +187,7 @@ class MCTS(object):
             prior, value = self.evaluator(next_action.next_state)
             next_action.expansion(prior, self.action_num)
         else:
-            value = 0
+            value = 0.
         t2 = time.time()
         if self.inverse:
             next_action.backpropagation(-value + 0.)