Mercurial > pylearn
view sparse_random_autoassociator/parameters.py @ 382:b4efd192d880
Moved xent loss to nnet_ups
author | Joseph Turian <turian@gmail.com> |
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date | Tue, 08 Jul 2008 01:58:16 -0400 |
parents | a1bbcde6b456 |
children |
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""" Parameters (weights) used by the L{Model}. """ import numpy import globals class Parameters: """ Parameters used by the L{Model}. """ def __init__(self, input_dimension=globals.INPUT_DIMENSION, hidden_dimension=globals.HIDDEN_DIMENSION, randomly_initialize=False, seed=globals.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(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) 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)