def trained_cat_dog_ANN(): n = FeedForwardNetwork() d = get_cat_dog_trainset() input_size = d.getDimension('input') n.addInputModule(LinearLayer(input_size, name='in')) n.addModule(SigmoidLayer(input_size + 1500, name='hidden')) n.addOutputModule(LinearLayer(2, name='out')) n.addConnection(FullConnection(n['in'], n['hidden'], name='c1')) n.addConnection(FullConnection(n['hidden'], n['out'], name='c2')) n.sortModules() n.convertToFastNetwork() print 'successful converted to fast network' t = BackpropTrainer(n, d, learningrate=0.0001) #, momentum=0.75) count = 0 while True: globErr = t.train() print globErr count += 1 if globErr < 0.01: break if count == 30: break exportCatDogANN(n) return n
def trained_cat_dog_ANN(): n = FeedForwardNetwork() d = get_cat_dog_trainset() input_size = d.getDimension('input') n.addInputModule(LinearLayer(input_size, name='in')) n.addModule(SigmoidLayer(input_size+1500, name='hidden')) n.addOutputModule(LinearLayer(2, name='out')) n.addConnection(FullConnection(n['in'], n['hidden'], name='c1')) n.addConnection(FullConnection(n['hidden'], n['out'], name='c2')) n.sortModules() n.convertToFastNetwork() print 'successful converted to fast network' t = BackpropTrainer(n, d, learningrate=0.0001)#, momentum=0.75) count = 0 while True: globErr = t.train() print globErr count += 1 if globErr < 0.01: break if count == 30: break exportCatDogANN(n) return n
def testMdlstm(self): net = FeedForwardNetwork() net.addInputModule(LinearLayer(1, name='in')) net.addModule(MDLSTMLayer(1, 1, name='hidden')) net.addOutputModule(LinearLayer(1, name='out')) net.addConnection(FullConnection(net['in'], net['hidden'])) net.addConnection(FullConnection(net['hidden'], net['out'])) net.sortModules() self.equivalence_feed_forward(net, net.convertToFastNetwork())
def testMdlstm(self): net = FeedForwardNetwork() net.addInputModule(LinearLayer(1, name='in')) net.addModule(MDLSTMLayer(1, 1, name='hidden')) net.addOutputModule(LinearLayer(1, name='out')) net.addConnection(FullConnection(net['in'], net['hidden'])) net.addConnection(FullConnection(net['hidden'], net['out'])) net.sortModules() self.equivalence_feed_forward(net, net.convertToFastNetwork())
def __init__(self, index, name, params): self.name = name self.index = index self.liste = []#ClassificationDataSet(17, 1, nb_classes=4) self.status_good = True self.number_of_moves = 0 self.number_of_sound_moves = 0 n = FeedForwardNetwork() self.inLayer = LinearLayer(17) self.hiddenLayer = SigmoidLayer(5) self.outLayer = LinearLayer(4) n.addInputModule(self.inLayer) n.addModule(self.hiddenLayer) n.addOutputModule(self.outLayer) from pybrain.structure import FullConnection in_to_hidden = FullConnection(self.inLayer, self.hiddenLayer) hidden_to_out = FullConnection(self.hiddenLayer, self.outLayer) n.addConnection(in_to_hidden) n.addConnection(hidden_to_out) n.sortModules() for j, i in enumerate(params[0]): n.connections[self.hiddenLayer][0].params[j] = i for j, i in enumerate(params[1]): n.connections[self.inLayer][0].params[j] = i n.convertToFastNetwork() self.n = n self.n.convertToFastNetwork()
def __init__(self, index, name, params): self.name = name self.index = index self.status_good = True n = FeedForwardNetwork() self.inLayer = LinearLayer(17) self.hiddenLayer = SigmoidLayer(5) self.outLayer = LinearLayer(4) n.addInputModule(self.inLayer) n.addModule(self.hiddenLayer) n.addOutputModule(self.outLayer) from pybrain.structure import FullConnection in_to_hidden = FullConnection(self.inLayer, self.hiddenLayer) hidden_to_out = FullConnection(self.hiddenLayer, self.outLayer) n.addConnection(in_to_hidden) n.addConnection(hidden_to_out) n.sortModules() for j, i in enumerate(params[0]): n.connections[self.hiddenLayer][0].params[j] = i for j, i in enumerate(params[1]): n.connections[self.inLayer][0].params[j] = i n.convertToFastNetwork() self.n = n # self.n.convertToFastNetwork()
def __init__(self, index, name, param): self.name = name self.index = index self.liste = []#ClassificationDataSet(17, 1, nb_classes=4) self.status_good = True self.number_of_moves = 0 self.number_of_sound_moves = 0 n = FeedForwardNetwork() # self.inLayer = LinearLayer(17) # self.hiddenLayer = SigmoidLayer(5) # self.outLayer = LinearLayer(4) # # # n.addInputModule(self.inLayer) # n.addModule(self.hiddenLayer) # n.addOutputModule(self.outLayer) self.inLayer = LinearLayer(17) self.hiddenLayer1 = SigmoidLayer(15) self.hiddenLayer2 = SigmoidLayer(15) self.hiddenLayer3 = SigmoidLayer(15) self.hiddenLayer4 = SigmoidLayer(15) self.hiddenLayer5 = SigmoidLayer(15) self.hiddenLayer6 = SigmoidLayer(15) self.outLayer = LinearLayer(4) n.addInputModule(self.inLayer) n.addModule(self.hiddenLayer1) n.addModule(self.hiddenLayer2) n.addModule(self.hiddenLayer3) n.addModule(self.hiddenLayer4) n.addModule(self.hiddenLayer5) n.addModule(self.hiddenLayer6) n.addOutputModule(self.outLayer) from pybrain.structure import FullConnection in_to_hidden = FullConnection(self.inLayer, self.hiddenLayer1) hidden_to_hidden1 = FullConnection(self.hiddenLayer1, self.hiddenLayer2) hidden_to_hidden2 = FullConnection(self.hiddenLayer2, self.hiddenLayer3) hidden_to_hidden3 = FullConnection(self.hiddenLayer3, self.hiddenLayer4) hidden_to_hidden4 = FullConnection(self.hiddenLayer4, self.hiddenLayer5) hidden_to_hidden5 = FullConnection(self.hiddenLayer5, self.hiddenLayer6) hidden_to_out = FullConnection(self.hiddenLayer6, self.outLayer) n.addConnection(in_to_hidden) n.addConnection(hidden_to_hidden1) n.addConnection(hidden_to_hidden2) n.addConnection(hidden_to_hidden3) n.addConnection(hidden_to_hidden4) n.addConnection(hidden_to_hidden5) n.addConnection(hidden_to_out) # in_to_hidden = FullConnection(self.inLayer, self.hiddenLayer) # hidden_to_out = FullConnection(self.hiddenLayer, self.outLayer) # n.addConnection(in_to_hidden) # n.addConnection(hidden_to_out) n.sortModules() print len(n.connections[self.inLayer][0].params) print len(n.connections[self.hiddenLayer1][0].params ) print len(n.connections[self.hiddenLayer2][0].params) print len(n.connections[self.hiddenLayer3][0].params) print len(n.connections[self.hiddenLayer4][0].params) print len(n.connections[self.hiddenLayer5][0].params) print len(n.connections[self.hiddenLayer6][0].params) for j, i in enumerate(param[0]): n.connections[self.inLayer][0].params[j] = i for j, i in enumerate(param[1]): n.connections[self.hiddenLayer1][0].params[j] = i for j, i in enumerate(param[2]): n.connections[self.hiddenLayer2][0].params[j] = i for j, i in enumerate(param[3]): n.connections[self.hiddenLayer3][0].params[j] = i for j, i in enumerate(param[4]): n.connections[self.hiddenLayer4][0].params[j] = i for j, i in enumerate(param[5]): n.connections[self.hiddenLayer5][0].params[j] = i for j, i in enumerate(param[6]): n.connections[self.hiddenLayer6][0].params[j] = i n.convertToFastNetwork() self.n = n self.n.convertToFastNetwork()