Is there开发者_如何学Go a way to save and recover a trained Neural Network in PyBrain, so that I don't have to retrain it each time I run the script?
PyBrain's Neural Networks can be saved and loaded using either python's built in pickle/cPickle module, or by using PyBrain's XML NetworkWriter.
# Using pickle
from pybrain.tools.shortcuts import buildNetwork
import pickle
net = buildNetwork(2,4,1)
fileObject = open('filename', 'w')
pickle.dump(net, fileObject)
fileObject.close()
fileObject = open('filename','r')
net = pickle.load(fileObject)
Note cPickle is implemented in C, and therefore should be much faster than pickle. Usage should mostly be the same as pickle, so just import and use cPickle instead.
# Using NetworkWriter
from pybrain.tools.shortcuts import buildNetwork
from pybrain.tools.customxml.networkwriter import NetworkWriter
from pybrain.tools.customxml.networkreader import NetworkReader
net = buildNetwork(2,4,1)
NetworkWriter.writeToFile(net, 'filename.xml')
net = NetworkReader.readFrom('filename.xml')
The NetworkWriter
and NetworkReader
work great. I noticed that upon saving and loading via pickle
, that the network is no longer changeable via training-functions. Thus, I would recommend using the NetworkWriter
-method.
NetworkWriter is the way to go. Using Pickle you can't retrain network as Jorg tells.
You need something like this:
from pybrain.tools.shortcuts import buildNetwork
from pybrain.tools.customxml import NetworkWriter
from pybrain.tools.customxml import NetworkReader
net = buildNetwork(4,6,1)
NetworkWriter.writeToFile(net, 'filename.xml')
net = NetworkReader.readFrom('filename.xml')
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