def setDelta(self, delta):
if (self.unitType != UnitType['HIDDEN']
and self.unitType != UnitType['OUTPUT']):
raise myerror.MyError("Invalid unit type!")
self.delta = delta
def getDelta(self):
if (self.unitType != UnitType['HIDDEN']
and self.unitType != UnitType['OUTPUT']):
raise myerror.MyError("Invalid unit type!")
return self.delta
def setInput(self, value):
if (self.unitType != UnitType['INPUT']
and self.unitType != UnitType['HIDDEN']
and self.unitType != UnitType['OUTPUT']):
raise myerror.MyError("Invalid unit type!")
self.inputValue = value
def getInput(self):
if (self.unitType != UnitType['INPUT']
and self.unitType != UnitType['HIDDEN']
and self.unitType != UnitType['OUTPUT']):
raise myerror.MyError("Invalid unit type!")
return self.inputValue
def getRightConnections(self):
if (self.unitType != UnitType['INPUT']
and self.unitType != UnitType['HIDDEN']
and self.unitType != UnitType['BIAS']):
raise myerror.MyError("Invalid unit type!")
return self.rightConnections
def getLeftConnections(self):
if (self.unitType != UnitType['HIDDEN']
and self.unitType != UnitType['OUTPUT']):
raise myerror.MyError("Invalid unit type!")
return self.leftConnections
def setRightConnections(self, connections):
if (self.unitType != UnitType['INPUT']
and self.unitType != UnitType['HIDDEN']
and self.unitType != UnitType['BIAS']):
raise myerror.MyError("Invalid unit type!")
self.rightConnections = connections
def setLeftConnections(self, connections):
if (self.unitType != UnitType['HIDDEN']
and self.unitType != UnitType['OUTPUT']):
raise myerror.MyError("Invalid unit type!")
self.leftConnections = connections
def __init__(self, param):
# check parameter
if param == None:
raise myerror.MyError("NUll parameter")
if ('numOfUnits' in param) == False:
raise myerror.MyError("numOfUnits must be specified")
if len(param['numOfUnits']) <= 2:
raise myerror.MyError("At least 1 hidden units must be specified")
# default weight
self.DEFAULT_WEIGHT = 0
# number of units
self.numOfUnits = param['numOfUnits']
# learning coefficient
self.learningCoefficient = 0.01
# mini batch size
self.miniBatchSize = 10
# connection objects
self.connections = {}
# unit objects
self.units = {}
# average of input value
self.inputMeans = []
if 'means' in param:
self.inputMeans = param['means']
# standard deviation of inputs value
self.inputSDs = []
if 'sds' in param:
self.inputSDs = param['sds']
# initialize all of processes
# all layers
layerArray = []
# initialize input layer
# lead is BIAS unit
inputUnitArray = []
inputUnitArray.append(unit.Unit(unit.UnitType['BIAS']))
for i in xrange(0, self.numOfUnits[0]):
inputUnitArray.append(unit.Unit(unit.UnitType['INPUT']))
layerArray.append(inputUnitArray)
# initialize hidden layers
# lead is BIAS unit
for j in xrange(1, (len(self.numOfUnits) - 1)):
hiddenUnitArray = []
hiddenUnitArray.append(unit.Unit(unit.UnitType['BIAS']))
for k in xrange(0, self.numOfUnits[j]):
hiddenUnitArray.append(unit.Unit(unit.UnitType['HIDDEN']))
layerArray.append(hiddenUnitArray)
# initialize output layer
outputUnitArray = []
for l in xrange(0, self.numOfUnits[len(self.numOfUnits) - 1]):
outputUnitArray.append(unit.Unit(unit.UnitType['OUTPUT']))
layerArray.append(outputUnitArray)
# unit objects
self.units = layerArray
# utility
dnnUtil = utility.Util()
# generation of connections
allConnectionArray = []
for m in xrange(0, (len(self.numOfUnits) - 1)):
connectionArray = []
for n in xrange(0, len(self.units[m])):
connArray = []
leftUnit = self.units[m][n]
for p in xrange(0, len(self.units[m + 1])):
rightUnit = self.units[m + 1][p]
if rightUnit.getUnitType() != unit.UnitType['BIAS']:
conn = connection.Connection()
conn.setRightUnit(rightUnit)
conn.setLeftUnit(leftUnit)
if leftUnit.getUnitType() == unit.UnitType['BIAS']:
conn.setWeight(self.DEFAULT_WEIGHT)
else:
conn.setWeight(self.DEFAULT_WEIGHT +
dnnUtil.rnorm(0, 1))
connArray.append(conn)
connTmpArray = rightUnit.getLeftConnections()
connTmpArray.append(conn)
rightUnit.setLeftConnections(connTmpArray)
connectionArray.append(connArray)
leftUnit.setRightConnections(connArray)
allConnectionArray.append(connectionArray)
self.connections = allConnectionArray
if 'weights' in param:
for s in xrange(0, len(self.connections)):
for t in xrange(0, len(self.connections[s])):
for u in xrange(0, len(self.connections[s][t])):
self.connections[s][t][u].setWeight(
param['weights'][s][t][u])