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New: MemoryBank

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This commit is contained in:
Dominik Moritz Roth 2022-04-15 14:14:41 +02:00
parent d164a59e31
commit 4912fbc0a4
2 changed files with 25 additions and 6 deletions
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12
ultimatetictactoe.py
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@ -180,8 +180,14 @@ class Model(nn.Module):
return y return y
if __name__=="__main__": if __name__=="__main__":
run = NeuralRuntime(TTTState()) init = TTTState()
run = NeuralRuntime(init)
run.game([0,1], 4) 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)

17
vacuumDecay.py
View File

@ -442,7 +442,7 @@ class Runtime():
bots = [None]*self.head.playersNum bots = [None]*self.head.playersNum
while self.head.getWinner()==None: while self.head.getWinner()==None:
self.turn(bots[self.head.curPlayer], calcDepth) self.turn(bots[self.head.curPlayer], calcDepth)
print(self.head.getWinner() + ' won!') print(str(self.head.getWinner()) + ' won!')
self.killWorker() self.killWorker()
class NeuralRuntime(Runtime): class NeuralRuntime(Runtime):
@ -510,9 +510,10 @@ class Trainer(Runtime):
return return
head = head.parent 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() loss_func = nn.MSELoss()
optimizer = optim.Adam(model.parameters(), lr) optimizer = optim.Adam(model.parameters(), lr)
if term==None:
term = self.buildDatasetFromModel(model, depth=calcDepth, exacity=exacity) term = self.buildDatasetFromModel(model, depth=calcDepth, exacity=exacity)
print('[*] Conditioning Brain...') print('[*] Conditioning Brain...')
for r in range(64): for r in range(64):
@ -555,3 +556,15 @@ class Trainer(Runtime):
model.load_state_dict(torch.load('brains/uttt.pth')) model.load_state_dict(torch.load('brains/uttt.pth'))
model.eval() model.eval()
self.main(model, startGen=0) 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)