def __init__(self,n_in,n_hidden): w=np.random.random_sample(n_hidden,n_in) b=np.zeros((n_hidden,1)) self.hidden=Layer(w,b) w=np.random.random_sample(n_in,n_hidden) b=np.zeros((n_in,1)) self.out=Layer(w,b) self.beta=3 self.lmb=0.001 self.sparsityParam=0.05 self.active=active.sigmoid() self.eta=0.01 return
def __init__(self,layers): if layers==None: raise TypeError('layers is none') length=len(layers) tmp_layers=[] for i in xrange(length): n_in=layers[i] n_out=layers[i+1] fanin=n_in*n_out sd=1.0/sqrt(fanin) w=sd*random.random_sample((n_in,n_out)) b=zeros((1,n_out)) this_layer=Layer(w,b) tmp_layers.append(this_layer) self.layers=tmp_layers self.active=sigmoid() self.Lambda=exp(-4) self.n_out=layers[len(layers)-1] self.eta=0.01 return