所以我现在正试图进行反向传播，但出于某种原因，我得到了一个输出，一个激活，但没有输出值。现在我只是在使用单层网络，只是一些简单的事情，但它似乎没有按照它的想法去做。
我创建了2组节点，node1和node2，添加了连接1到2的连接。在下面的模式上训练它，更新权重，更新输入，更新激活，然后输出。但我得到了0。
#
# Preparations
#
import random
import math
import pygame
import sys
node1 = []
node2 = []
node3 = []
node4 = []
node5 = []
set1 = []
set2 = []
set3 = []
NUMNODES = 10
mu = .5
eta = .1
#
# Node Class
#
class Node(object):
def __init__(self,name=None):
self.name=name
self.activation_threshold=0.0
self.net_input=0.0
self.net_output=0.0
self.outgoing_connections=[]
self.incoming_connections=[]
self.activation=None
def __str__(self):
return self.name
def addconnection(self,sender,weight=0.0):
self.incoming_connections.append(Connection(sender,self,weight))
self.outgoing_connections.append(Connection(self,sender,weight))
def update_input(self):
self.net_input=0.0
for conn in self.incoming_connections:
self.net_input += conn.weight * conn.sender.activation
## print 'Input for node', str(self), 'is', self.net_input
############################# Is this necessary? ####################
def update_output(self):
self.net_output=0.0
for conn in self.outgoing_connections:
self.net_output += conn.weight * self.activation
###########################################################################
def update_activation(self):
if self.net_input > self.activation_threshold:
self.activation = 1.0
else:
self.activation = 0.0
## print 'Activation :', self.activation
## def update_weight(self):
## for i in self.incoming_connections:
## i.weight += self.delta_wt
## self.delta_wt = mu
def update_weight(self):
for i in self.incoming_connections:
i.weight += (2*i.reciever.activation - 1)*(2*i.sender.activation-1)
## print 'Weight of', str(i.reciever), 'to', str(i.sender), 'is', i.weight
def update_error(self):
pass
#
# Connection Class
#
class Connection(object):
def __init__(self, sender, reciever, weight):
self.weight=weight
self.sender=sender
self.reciever=reciever
def __str__(self):
string = "Connection from " + str(self.sender) + " to " + str(self.reciever) + ", weight = " + str(self.weight)
return string
#######################################################################################
#
# Creating Nodes & Connections
#
#######################################################################################
def set_activations(act_vector):
for i in xrange(len(act_vector)):
node1[i].activation = act_vector[i]
node2[i].activation = act_vector[i]
for i in xrange(NUMNODES):
node1.append(Node(str(i)))
node2.append(Node(str(i)))
node3.append(Node(str(i)))
node4.append(Node(str(i)))
node5.append(Node(str(i)))
for i in xrange(NUMNODES):
for j in xrange(NUMNODES):
if i!=j:
node1[i].addconnection(node2[j])
node3[i].addconnection(node4[j])
node4[i].addconnection(node5[j])
#######################################################################################
#
# Training Patterns
#
#######################################################################################
"""Non-Overlapping Categories"""
cata11=[0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0]
set1.append(cata11)
cata12=[0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0]
set1.append(cata12)
catb11=[0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0]
set1.append(catb11)
catb12=[0.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0]
set1.append(catb12)
catc11=[0.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0]
set1.append(catc11)
catc12=[0.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0]
set1.append(catc12)
catd11=[0.0,1.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0]
set1.append(catd11)
catd12=[1.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0]
set1.append(catd12)
"""Linearly Independent Instances and Linearly Separable Categories"""
cata21=[1.0,1.0,0.0,1.0,0.0,0.0,0.0,0.0,0.0,1.0]
set2.append(cata21)
cata22=[1.0,1.0,0.0,0.0,1.0,0.0,0.0,0.0,0.0,1.0]
set2.append(cata22)
catb21=[1.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,1.0,0.0]
set2.append(catb21)
catb22=[1.0,1.0,0.0,0.0,0.0,0.0,0.0,0.0,1.0,0.0]
set2.append(catb22)
catc21=[1.0,0.0,1.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0]
set2.append(catc21)
catc22=[1.0,0.0,1.0,0.0,1.0,0.0,0.0,1.0,0.0,0.0]
set2.append(catc22)
catd21=[1.0,0.0,1.0,0.0,0.0,1.0,1.0,0.0,0.0,0.0]
set2.append(catd21)
catd22=[1.0,0.0,1.0,0.0,0.0,0.0,1.0,0.0,0.0,0.0]
set2.append(catd22)
"""Not Linearly Separable Categories"""
cata31=[1.0,1.0,1.0,1.0,1.0,0.0,0.0,0.0,0.0,0.0]
set3.append(cata31)
cata32=[0.0,0.0,0.0,0.0,0.0,1.0,1.0,1.0,1.0,1.0]
set3.append(cata32)
catb31=[1.0,1.0,0.0,1.0,1.0,0.0,0.0,1.0,0.0,0.0]
set3.append(catb31)
catb32=[0.0,0.0,1.0,0.0,0.0,1.0,1.0,0.0,1.0,1.0]
set3.append(catb32)
set_activations(cata11)
for thing in node1:
thing.update_weight()
set_activations(cata12)
for thing in node1:
thing.update_weight()
set_activations(catb11)
for thing in node1:
thing.update_weight()
set_activations(catb12)
for thing in node1:
thing.update_weight()
set_activations(catc11)
for thing in node1:
thing.update_weight()
set_activations(catc12)
for thing in node1:
thing.update_weight()
set_activations(catd11)
for thing in node1:
thing.update_weight()
set_activations(catd12)
for thing in node1:
thing.update_weight()
#######################################################################################
#
# Updating Network
#
#######################################################################################
for i in node1:
i.update_input()
print 'Node', str(i), 'Input : ', i.net_input
i.update_activation()
print 'Act:', i.activation
i.update_output()
print 'Output', i.net_output
out_file=open('output.txt','w')
out_file.close()