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
