Mercurial > pylearn

comparison sandbox/rbm/parameters.py @ 406:c2e6a8fcc35e

Find changesets by keywords (author, files, the commit message), revision number or hash, or revset expression.
Globals are now parameters for the RBM model
author Joseph Turian <turian@gmail.com>
date Thu, 10 Jul 2008 02:10:23 -0400
parents e0c9357456e0
children
comparison
equal deleted inserted replaced
405:be4209cd568f 406:c2e6a8fcc35e
1 """ 1 """
2 Parameters (weights) used by the L{Model}. 2 Parameters (weights) used by the L{Model}.
3 """ 3 """
4 4
5 import numpy 5 import numpy
6 import globals
7 6
8 class Parameters: 7 class Parameters:
9 """ 8 """
10 Parameters used by the L{Model}. 9 Parameters used by the L{Model}.
11 """ 10 """
12 def __init__(self, input_dimension=globals.INPUT_DIMENSION, hidden_dimension=globals.HIDDEN_DIMENSION, randomly_initialize=False, seed=globals.SEED): 11 def __init__(self, input_dimension, hidden_dimension, randomly_initialize, random_seed):
13 """ 12 """
14 Initialize L{Model} parameters. 13 Initialize L{Model} parameters.
15 @param randomly_initialize: If True, then randomly initialize 14 @param randomly_initialize: If True, then randomly initialize
16 according to the given seed. If False, then just use zeroes. 15 according to the given random_seed. If False, then just use zeroes.
17 """ 16 """
18 if randomly_initialize: 17 if randomly_initialize:
19 numpy.random.seed(seed) 18 numpy.random.random_seed(random_seed)
20 self.w = (numpy.random.rand(input_dimension, hidden_dimension)-0.5)/input_dimension 19 self.w = (numpy.random.rand(input_dimension, hidden_dimension)-0.5)/input_dimension
21 self.b = numpy.zeros((1, hidden_dimension)) 20 self.b = numpy.zeros((1, hidden_dimension))
22 self.c = numpy.zeros((1, input_dimension)) 21 self.c = numpy.zeros((1, input_dimension))
23 else: 22 else:
24 self.w = numpy.zeros((input_dimension, hidden_dimension)) 23 self.w = numpy.zeros((input_dimension, hidden_dimension))