KeyError in sortModules

[ghost]

I have an issue with the sortModules method throwing a KeyError.

Following the tutorial example, I created a script with the following:

#! /usr/bin/env python
# -*- coding: utf-8 -*-

import sys
import scipy
import numpy as np

print "\nPython version: %s" % sys.version
print "Numpy version: %s" % np.version.version
print "Scipy version: %s" % scipy.version.version

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

# Create network
nn = FeedForwardNetwork()

# Set network parameters
INPUT_NDS = 2
HIDDEN_NDS = 3
OUTPUT_NDS = 1

# Create Feed Forward Network layers
inLayer = LinearLayer(INPUT_NDS)
hiddenLayer = SigmoidLayer(HIDDEN_NDS)
outLayer = LinearLayer(OUTPUT_NDS)

# Fully connect all layers
in_to_hidden = FullConnection(inLayer, hiddenLayer)
hidden_to_out = FullConnection(hiddenLayer, outLayer)

# Add the connected layers to the network 
nn.addConnection(in_to_hidden)
nn.addConnection(hidden_to_out)

# Sort modules to prepare the NN for use
nn.sortModules()

Which gives me:
Python version: 2.6.5 (r265:79063, Apr 16 2010, 13:57:41)
[GCC 4.4.3]
Numpy version: 1.3.0
Scipy version: 0.7.0
Traceback (most recent call last):
File "/tmp/py7317Q6c", line 46, in
nn.sortModules()
File "/usr/local/lib/python2.6/dist-packages/PyBrain-0.3-py2.6.egg/pybrain/structure/networks/network.py", line 224, in sortModules
self._topologicalSort()
File "/usr/local/lib/python2.6/dist-packages/PyBrain-0.3-py2.6.egg/pybrain/structure/networks/network.py", line 188, in _topologicalSort
graph[c.inmod].append(c.outmod)
KeyError: <LinearLayer 'LinearLayer-3'>

I have the latest version of pybrain installed, so this seems strange. Especially as I when use the shortcut:

from pybrain.tools.shortcuts import buildNetwork

[schaul]

You need to do nn.addModule(xLayer) for all the modules, before adding the connections.

[ghost]

Thanks for the quick reply.
I guess I should read the documentation a little more closely!
Sorry for the noob question and thanks for your help!

[schaul]

You're welcome!