Mercurial > pylearn
annotate sandbox/simple_autoassociator/parameters.py @ 436:d7ed780364b3
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author | Olivier Breuleux <breuleuo@iro.umontreal.ca> |
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date | Wed, 06 Aug 2008 19:39:14 -0400 |
parents | 4f61201fa9a9 |
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rev | line source |
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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 """ |
a1bbcde6b456
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Joseph Turian <turian@gmail.com>
parents:
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9 Parameters used by the L{Model}. |
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Joseph Turian <turian@gmail.com>
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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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Joseph Turian <turian@gmail.com>
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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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parents:
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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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parents:
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25 self.w1 = numpy.zeros((input_dimension, hidden_dimension)) |
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parents:
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26 self.w2 = numpy.zeros((hidden_dimension, input_dimension)) |
a1bbcde6b456
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Joseph Turian <turian@gmail.com>
parents:
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27 self.b1 = numpy.zeros(hidden_dimension) |
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parents:
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28 self.b2 = numpy.zeros(input_dimension) |
387 | 29 |
30 def __str__(self): | |
31 s = "" | |
32 s += "w1: %s\n" % self.w1 | |
33 s += "b1: %s\n" % self.b1 | |
34 s += "w2: %s\n" % self.w2 | |
35 s += "b2: %s\n" % self.b2 | |
36 return s |