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from pyrobot.brain.conx import *
from pyrobot.brain.ravq import *
n = SRN()
n.setSequenceType("ordered-continuous")
n.addLayers(16,2,2)
n.loadDataFromFile('input_target.dat')
n.setEpsilon(0.2)
n.setMomentum(0.9)
n.setTolerance(0.05)
n.setLearning(1)
ravq = ARAVQ(3, .2, 1.6, .05)
ravq.setAddModels(1)
ravq.setHistory(1)
ravq.setMask([1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,8,8])
fp = open('balanced.dat','w')
counter = 0
buffer = []
bufferIndex = 0
method = 1
def saveListToFile(ls, file):
for i in range(len(ls)):
file.write(str(ls[i]) + " ")
file.write("\n")
for x in n.loadOrder:
inputs = n.inputs[x]
targets = n.targets[x]
ravq.input(inputs + targets)
if method:
if ravq.getNewWinner(): # is 1 if the winner is a new winner, 0 otherwise
if len(buffer) >= 100:
buffer = buffer[1:] + [inputs + targets]
else:
buffer.append(inputs + targets)
if len(buffer) > 0: # cycle through current buffer
array = buffer[bufferIndex]
bufferIndex = (bufferIndex + 1) % len(buffer)
n.step(input = array[:16], output = array[16:])
saveListToFile(array, fp)
if x > 50000: # train for 50000 steps
break
else:
if ravq.getHistoryLength() > 0:
array = ravq.getHistory(bufferIndex)
bufferIndex = (bufferIndex + 1) % ravq.getHistoryLength()
n.step(input = array[:16], output = array[16:])
saveListToFile(array, fp)
if x > 50000:
break
print " Count: ", x
print " Steps: ", n.count
print " Number of model vectors: ", len(ravq.models)
n.saveWeightsToFile('network.wts')
fp.close() |
