view sandbox/sparse_random_autoassociator/parameters.py @ 432:8e4d2ebd816a

added a test for LinearRegression
author Yoshua Bengio <bengioy@iro.umontreal.ca>
date Tue, 29 Jul 2008 11:16:05 -0400
parents 36baeb7125a4
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)