Mercurial > pylearn

annotate sandbox/simple_autoassociator/parameters.py @ 448:0961d4b56ec5

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Added some documentation
author Joseph Turian <turian@gmail.com>
date Wed, 03 Sep 2008 17:08:54 -0400
parents 4f61201fa9a9
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1 """
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2 Parameters (weights) used by the L{Model}.
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3 """
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4
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5 import numpy
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6
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7 class Parameters:
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8 """
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9 Parameters used by the L{Model}.
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10 """
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11 def __init__(self, input_dimension, hidden_dimension, randomly_initialize, random_seed):
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12 """
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13 Initialize L{Model} parameters.
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14 @param randomly_initialize: If True, then randomly initialize
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15 according to the given seed. If False, then just use zeroes.
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16 """
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17 if randomly_initialize:
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18 numpy.random.seed(random_seed)
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19 self.w1 = (numpy.random.rand(input_dimension, hidden_dimension)-0.5)/input_dimension
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20 self.w2 = (numpy.random.rand(hidden_dimension, input_dimension)-0.5)/hidden_dimension
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21 self.b1 = numpy.zeros(hidden_dimension)
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22 self.b2 = numpy.zeros(input_dimension)
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23 #self.b2 = numpy.array([10, 0, 0, -10])
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24 else:
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25 self.w1 = numpy.zeros((input_dimension, hidden_dimension))
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26 self.w2 = numpy.zeros((hidden_dimension, input_dimension))
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27 self.b1 = numpy.zeros(hidden_dimension)
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28 self.b2 = numpy.zeros(input_dimension)
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29
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30 def __str__(self):
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31 s = ""
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32 s += "w1: %s\n" % self.w1
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33 s += "b1: %s\n" % self.b1
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34 s += "w2: %s\n" % self.w2
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35 s += "b2: %s\n" % self.b2
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36 return s