def initParams(self):
	"""
	Initialize parameters using 6/sqrt(fanin+fanout)
	"""
        sizes = [self.inputDim]+self.layerSizes+[self.outputDim]
        scales = [gp.sqrt(6)/gp.sqrt(n+m) for n,m in zip(sizes[:-1],sizes[1:])]
        self.stack = [[gp.rand(m,n)*2*s-s,gp.zeros((m,1))] \
                            for n,m,s in zip(sizes[:-1],sizes[1:],scales)]
        self.hActs = [gp.empty((s,self.mbSize)) for s in sizes]

        if self.train:
            self.deltas = [gp.empty((s,self.mbSize)) for s in sizes[1:]]
            self.grad = [[gp.empty(w.shape),gp.empty(b.shape)] for w,b in self.stack]
dataset/ETHPy150Open amaas/stanford-ctc/py-simple-hybrid/nnet.py/NNet.initParams/original