From 4912fbc0a46761b647d742b4d2367fecfc855abf Mon Sep 17 00:00:00 2001
From: Dominik Roth <dominik.roth.dev@gmail.com>
Date: Fri, 15 Apr 2022 14:14:41 +0200
Subject: [PATCH] New: MemoryBank

---
 ultimatetictactoe.py | 12 +++++++++---
 vacuumDecay.py       | 19 ++++++++++++++++---
 2 files changed, 25 insertions(+), 6 deletions(-)

diff --git a/ultimatetictactoe.py b/ultimatetictactoe.py
index 7e327d0..571c131 100644
--- a/ultimatetictactoe.py
+++ b/ultimatetictactoe.py
@@ -180,8 +180,14 @@ class Model(nn.Module):
         return y
 
 if __name__=="__main__":
-    run = NeuralRuntime(TTTState())
+    init = TTTState()
+    run = NeuralRuntime(init)
     run.game([0,1], 4)
 
-    #trainer = Trainer(TTTState())
-    #trainer.train()
+
+    print("[!] Your knowledge will be assimilated!!!")
+    trainer = Trainer(init)
+    trainer.train()
+    trainer.trainFromTerm(run.head)
+    print('[!] I have become smart. Destroyer of human Ultimate-TicTacToe players!')
+    trainer.saveToMemoryBank(term)
diff --git a/vacuumDecay.py b/vacuumDecay.py
index 2b20a2c..a14cc75 100644
--- a/vacuumDecay.py
+++ b/vacuumDecay.py
@@ -442,7 +442,7 @@ class Runtime():
             bots = [None]*self.head.playersNum
         while self.head.getWinner()==None:
             self.turn(bots[self.head.curPlayer], calcDepth)
-        print(self.head.getWinner() + ' won!')
+        print(str(self.head.getWinner()) + ' won!')
         self.killWorker()
 
 class NeuralRuntime(Runtime):
@@ -510,10 +510,11 @@ class Trainer(Runtime):
                 return
             head = head.parent
 
-    def trainModel(self, model, lr=0.00005, cut=0.01, calcDepth=4, exacity=5):
+    def trainModel(self, model, lr=0.00005, cut=0.01, calcDepth=4, exacity=5, term=None):
         loss_func = nn.MSELoss()
         optimizer = optim.Adam(model.parameters(), lr)
-        term = self.buildDatasetFromModel(model, depth=calcDepth, exacity=exacity)
+        if term==None:
+            term = self.buildDatasetFromModel(model, depth=calcDepth, exacity=exacity)
         print('[*] Conditioning Brain...')
         for r in range(64):
             loss_sum = 0
@@ -555,3 +556,15 @@ class Trainer(Runtime):
         model.load_state_dict(torch.load('brains/uttt.pth'))
         model.eval()
         self.main(model, startGen=0)
+
+    def trainFromTerm(self, term):
+        model = self.rootNode.state.getModel()
+        model.load_state_dict(torch.load('brains/uttt.pth'))
+        model.eval()
+        self.universe.scoreProvider = 'neural'
+        self.trainModel(model, calcDepth=4, exacity=10, term=term)
+
+    def saveToMemoryBank(self, term):
+        with open('memoryBank/uttt/'+datetime.datetime.now().strftime('%Y-%m-%d_%H:%M:%S')+'_'+str(int(random.random()*99999))+'.vdm', 'wb') as f:
+            pickel.dump(term, f)
+