Pybrain 简明教程

PyBrain - Connections

连接类似于层；唯一的不同是，它在网络中将数据从一个节点转移到另一个节点。

A connection works similar to a layer; an only difference is that it shifts the data from one node to the other in a network.

在此章节，我们将学习：

In this chapter, we are going to learn about −

Understanding Connections
Creating Connections

Understanding Connections

下面是一个在创建网络时使用连接的工作示例。

Here is a working example of connections used while creating a network.

Example

ffy.py

from pybrain.structure import FeedForwardNetwork
from pybrain.structure import LinearLayer, SigmoidLayer
from pybrain.structure import FullConnection

network = FeedForwardNetwork()

#creating layer for input => 2 , hidden=> 3 and output=>1
inputLayer = LinearLayer(2)
hiddenLayer = SigmoidLayer(3)
outputLayer = LinearLayer(1)

#adding the layer to feedforward network
network.addInputModule(inputLayer)
network.addModule(hiddenLayer)
network.addOutputModule(outputLayer)

#Create connection between input ,hidden and output
input_to_hidden = FullConnection(inputLayer, hiddenLayer)
hidden_to_output = FullConnection(hiddenLayer, outputLayer)

#add connection to the network
network.addConnection(input_to_hidden)
network.addConnection(hidden_to_output)
network.sortModules()

print(network)

Output

C:\pybrain\pybrain\src>python ffn.py
FeedForwardNetwork-6
Modules:
[<LinearLayer 'LinearLayer-3'>, <SigmoidLayer 'SigmoidLayer-7'>,
   <LinearLayer 'LinearLayer-8'>]
Connections:
[<FullConnection 'FullConnection-4': 'SigmoidLayer-7' -> 'LinearLayer-8'>,
   <FullConnection 'FullConnection-5': 'LinearLayer-3' -> 'SigmoidLayer-7'>]

Creating Connections

在 Pybrain 中，我们可以使用如下所示的连接模块来创建连接：

In Pybrain, we can create connections by using the connection module as shown below −

Example

connect.py

from pybrain.structure.connections.connection import Connection
class YourConnection(Connection):
   def __init__(self, *args, **kwargs):
      Connection.__init__(self, *args, **kwargs)
   def _forwardImplementation(self, inbuf, outbuf):
      outbuf += inbuf
   def _backwardImplementation(self, outerr, inerr, inbuf):
      inerr += outer

要创建一个连接，有 2 种方法 — _forwardImplementation() 和 _backwardImplementation()。

To create a connection, there are 2 methods — _forwardImplementation() and _backwardImplementation().

_forwardImplementation() 在输入模块的输出缓冲器（即 inbuf）和输出模块的输入缓冲器（即 outbuf）中调用。inbuf 被添加到输出模块 outbuf。

The _forwardImplementation() is called with the output buffer of the incoming module which is inbuf, and the input buffer of the outgoing module called outbuf. The inbuf is added to the outgoing module outbuf.

_backwardImplementation() 在 outerr、inerr 和 inbuf 中调用。输出模块错误在 _backwardImplementation() 中添加到输入模块错误中。

The _backwardImplementation() is called with outerr, inerr, and inbuf. The outgoing module error is added to the incoming module error in _backwardImplementation().

现在让我们在网络中使用 YourConnection 。

Let us now use the YourConnection in a network.

testconnection.py

from pybrain.structure import FeedForwardNetwork
from pybrain.structure import LinearLayer, SigmoidLayer
from connect import YourConnection

network = FeedForwardNetwork()

#creating layer for input => 2 , hidden=> 3 and output=>1
inputLayer = LinearLayer(2)
hiddenLayer = SigmoidLayer(3)
outputLayer = LinearLayer(1)

#adding the layer to feedforward network
network.addInputModule(inputLayer)
network.addModule(hiddenLayer)
network.addOutputModule(outputLayer)

#Create connection between input ,hidden and output
input_to_hidden = YourConnection(inputLayer, hiddenLayer)
hidden_to_output = YourConnection(hiddenLayer, outputLayer)

#add connection to the network
network.addConnection(input_to_hidden)
network.addConnection(hidden_to_output)
network.sortModules()

print(network)

Output

C:\pybrain\pybrain\src>python testconnection.py
FeedForwardNetwork-6
Modules:
[<LinearLayer 'LinearLayer-3'>, <SigmoidLayer 'SigmoidLayer-7'>,
   <LinearLayer 'LinearLayer-8'>]
Connections:
[<YourConnection 'YourConnection-4': 'LinearLayer-3' -> 'SigmoidLayer-7'>,
   <YourConnection 'YourConnection-5': 'SigmoidLayer-7' -> 'LinearLayer-8'>]