Mercurial > pylearn
view sandbox/simple_autoassociator/parameters.py @ 437:2d8490d76b3e
added two methods to make_test_datasets
author | Olivier Breuleux <breuleuo@iro.umontreal.ca> |
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date | Wed, 06 Aug 2008 19:39:36 -0400 |
parents | 4f61201fa9a9 |
children |
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""" Parameters (weights) used by the L{Model}. """ import numpy class Parameters: """ Parameters used by the L{Model}. """ def __init__(self, input_dimension, hidden_dimension, randomly_initialize, random_seed): """ Initialize L{Model} parameters. @param randomly_initialize: If True, then randomly initialize according to the given seed. If False, then just use zeroes. """ if randomly_initialize: numpy.random.seed(random_seed) self.w1 = (numpy.random.rand(input_dimension, hidden_dimension)-0.5)/input_dimension self.w2 = (numpy.random.rand(hidden_dimension, input_dimension)-0.5)/hidden_dimension self.b1 = numpy.zeros(hidden_dimension) self.b2 = numpy.zeros(input_dimension) #self.b2 = numpy.array([10, 0, 0, -10]) else: self.w1 = numpy.zeros((input_dimension, hidden_dimension)) self.w2 = numpy.zeros((hidden_dimension, input_dimension)) self.b1 = numpy.zeros(hidden_dimension) self.b2 = numpy.zeros(input_dimension) def __str__(self): s = "" s += "w1: %s\n" % self.w1 s += "b1: %s\n" % self.b1 s += "w2: %s\n" % self.w2 s += "b2: %s\n" % self.b2 return s