annotate sandbox/simple_autoassociator/main.py @ 425:e2b46a8f2b7b

Debugging kernel regression
author Yoshua Bengio <bengioy@iro.umontreal.ca>
date Sat, 19 Jul 2008 17:57:46 -0400
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1 #!/usr/bin/python
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2 """
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3 A simple autoassociator.
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4
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5 The learned model is::
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6 h = sigmoid(dot(x, w1) + b1)
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7 y = sigmoid(dot(h, w2) + b2)
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8
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9 Binary xent loss.
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10 """
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11
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12
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13 import numpy
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14
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15 nonzero_instances = []
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16 nonzero_instances.append({0: 1, 1: 1})
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17 nonzero_instances.append({0: 1, 2: 1})
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18
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19 #nonzero_instances.append({1: 0.1, 5: 0.5, 9: 1})
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20 #nonzero_instances.append({2: 0.3, 5: 0.5, 8: 0.8})
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21 ##nonzero_instances.append({1: 0.2, 2: 0.3, 5: 0.5})
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23 import model
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24 model = model.Model(input_dimension=10, hidden_dimension=4)
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26 for i in xrange(100000):
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27 # # Select an instance
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28 # instance = nonzero_instances[i % len(nonzero_instances)]
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29
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30 # Update over instance
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31 model.update(nonzero_instances)