def createNet(self):
""" Set up the structure of the network """
net = Network()
Network.unregisterRegion(ImageSensor.__name__)
Network.registerRegion(ImageSensor)
imageSensorParams = copy.deepcopy(DEFAULT_IMAGESENSOR_PARAMS)
if self.loggingDir is not None:
imageSensorParams["logDir"] = "sensorImages/" + self.loggingDir
imageSensorParams["logOutputImages"] = 1
imageSensorParams["logOriginalImages"] = 1
imageSensorParams["logFilteredImages"] = 1
imageSensorParams["logLocationImages"] = 1
imageSensorParams["logLocationOnOriginalImage"] = 1
net.addRegion("sensor", "py.ImageSensor",
yaml.dump(imageSensorParams))
net.addRegion("SP", "py.SPRegion", yaml.dump(DEFAULT_SP_PARAMS))
net.addRegion("classifier","py.KNNClassifierRegion",
yaml.dump(DEFAULT_CLASSIFIER_PARAMS))
net.link("sensor", "SP", "UniformLink", "",
srcOutput = "dataOut", destInput = "bottomUpIn")
net.link("SP", "classifier", "UniformLink", "",
srcOutput = "bottomUpOut", destInput = "bottomUpIn")
net.link("sensor", "classifier", "UniformLink", "",
srcOutput = "categoryOut", destInput = "categoryIn")
self.net = net
self.networkSensor = self.net.regions["sensor"]
self.networkSP = self.net.regions["SP"]
self.networkClassifier = self.net.regions["classifier"]
def runExperiment():
Network.unregisterRegion("ImageSensor")
Network.registerRegion(ImageSensor)
Network.registerRegion(PCANode)
inputSize = 8
net = Network()
sensor = net.addRegion(
"sensor", "py.ImageSensor",
"{ width: %d, height: %d }" % (inputSize, inputSize))
params = ("{bottomUpCount: %s, "
" SVDSampleCount: 5, "
" SVDDimCount: 2}" % inputSize)
pca = net.addRegion("pca", "py.PCANode", params)
linkParams = "{ mapping: in, rfSize: [%d, %d] }" % (inputSize, inputSize)
net.link("sensor", "pca", "UniformLink", linkParams, "dataOut",
"bottomUpIn")
net.initialize()
for i in range(10):
pca.getSelf()._testInputs = numpy.random.random([inputSize])
net.run(1)
print s.sendRequest("nodeOPrint pca_node")
def runExperiment():
Network.unregisterRegion("ImageSensor")
Network.registerRegion(ImageSensor)
Network.registerRegion(PCANode)
inputSize = 8
net = Network()
sensor = net.addRegion(
"sensor", "py.ImageSensor" ,
"{ width: %d, height: %d }" % (inputSize, inputSize))
params = ("{bottomUpCount: %s, "
" SVDSampleCount: 5, "
" SVDDimCount: 2}" % inputSize)
pca = net.addRegion("pca", "py.PCANode", params)
linkParams = "{ mapping: in, rfSize: [%d, %d] }" % (inputSize, inputSize)
net.link("sensor", "pca", "UniformLink", linkParams, "dataOut", "bottomUpIn")
net.initialize()
for i in range(10):
pca.getSelf()._testInputs = numpy.random.random([inputSize])
net.run(1)
print s.sendRequest("nodeOPrint pca_node")
def createNet(self):
""" Set up the structure of the network """
net = Network()
Network.unregisterRegion(SaccadeSensor.__name__)
Network.registerRegion(SaccadeSensor)
Network.registerRegion(TMRegion)
imageSensorParams = copy.deepcopy(DEFAULT_IMAGESENSOR_PARAMS)
if self.loggingDir is not None:
imageSensorParams["logDir"] = "sensorImages/" + self.loggingDir
imageSensorParams["logOutputImages"] = 1
imageSensorParams["logOriginalImages"] = 1
imageSensorParams["logFilteredImages"] = 1
imageSensorParams["logLocationImages"] = 1
imageSensorParams["logLocationOnOriginalImage"] = 1
net.addRegion("sensor", "py.SaccadeSensor",
yaml.dump(imageSensorParams))
sensor = net.regions["sensor"].getSelf()
DEFAULT_SP_PARAMS["columnCount"] = sensor.getOutputElementCount("dataOut")
net.addRegion("SP", "py.SPRegion", yaml.dump(DEFAULT_SP_PARAMS))
sp = net.regions["SP"].getSelf()
DEFAULT_TM_PARAMS["columnDimensions"] = (sp.getOutputElementCount("bottomUpOut"),)
net.addRegion("TM", "py.TMRegion", yaml.dump(DEFAULT_TM_PARAMS))
net.addRegion("classifier","py.KNNClassifierRegion",
yaml.dump(DEFAULT_CLASSIFIER_PARAMS))
net.link("sensor", "SP", "UniformLink", "",
srcOutput="dataOut", destInput="bottomUpIn")
net.link("SP", "TM", "UniformLink", "",
srcOutput="bottomUpOut", destInput="activeColumns")
net.link("sensor", "TM", "UniformLink", "",
srcOutput="saccadeOut", destInput="activeExternalCells")
net.link("TM", "classifier", "UniformLink", "",
srcOutput="predictedActiveCells", destInput="bottomUpIn")
net.link("sensor", "classifier", "UniformLink", "",
srcOutput="categoryOut", destInput="categoryIn")
self.net = net
self.networkSensor = self.net.regions["sensor"]
self.networkSP = self.net.regions["SP"]
self.networkTM = self.net.regions["TM"]
self.networkClassifier = self.net.regions["classifier"]
def loadFromFile(self, filename):
""" Load a serialized network
:param filename: Where the network should be loaded from
"""
print "Loading network from {file}...".format(file=filename)
Network.unregisterRegion(SaccadeSensor.__name__)
Network.registerRegion(SaccadeSensor)
Network.registerRegion(TMRegion)
self.net = Network(filename)
self.networkSensor = self.net.regions["sensor"]
self.networkSensor.setParameter("numSaccades", SACCADES_PER_IMAGE_TESTING)
self.networkSP = self.net.regions["SP"]
self.networkClassifier = self.net.regions["classifier"]
self.numCorrect = 0
def loadFromFile(self, filename):
""" Load a serialized network
:param filename: Where the network should be loaded from
"""
print "Loading network from {file}...".format(file=filename)
Network.unregisterRegion(SaccadeSensor.__name__)
Network.registerRegion(SaccadeSensor)
Network.registerRegion(ExtendedTMRegion)
self.net = Network(filename)
self.networkSensor = self.net.regions["sensor"]
self.networkSensor.setParameter("numSaccades", SACCADES_PER_IMAGE_TESTING)
self.networkSP = self.net.regions["SP"]
self.networkClassifier = self.net.regions["classifier"]
self.numCorrect = 0
def createNet(self):
""" Set up the structure of the network """
net = Network()
Network.unregisterRegion(SaccadeSensor.__name__)
Network.registerRegion(SaccadeSensor)
Network.unregisterRegion(ExtendedTMRegion.__name__)
Network.registerRegion(ExtendedTMRegion)
Network.unregisterRegion(ColumnPoolerRegion.__name__)
Network.registerRegion(ColumnPoolerRegion)
imageSensorParams = copy.deepcopy(DEFAULT_IMAGESENSOR_PARAMS)
if self.loggingDir is not None:
imageSensorParams["logDir"] = "sensorImages/" + self.loggingDir
imageSensorParams["logOutputImages"] = 1
imageSensorParams["logOriginalImages"] = 1
imageSensorParams["logFilteredImages"] = 1
imageSensorParams["logLocationImages"] = 1
imageSensorParams["logLocationOnOriginalImage"] = 1
net.addRegion("sensor", "py.SaccadeSensor",
yaml.dump(imageSensorParams))
sensor = net.regions["sensor"].getSelf()
DEFAULT_SP_PARAMS["columnCount"] = sensor.getOutputElementCount(
"dataOut")
net.addRegion("SP", "py.SPRegion", yaml.dump(DEFAULT_SP_PARAMS))
sp = net.regions["SP"].getSelf()
DEFAULT_TM_PARAMS["columnDimensions"] = (
sp.getOutputElementCount("bottomUpOut"), )
DEFAULT_TM_PARAMS["basalInputWidth"] = sensor.getOutputElementCount(
"saccadeOut")
net.addRegion("TM", "py.ExtendedTMRegion",
yaml.dump(DEFAULT_TM_PARAMS))
net.addRegion("TP", "py.ColumnPoolerRegion",
yaml.dump(DEFAULT_TP_PARAMS))
net.addRegion("classifier", "py.KNNClassifierRegion",
yaml.dump(DEFAULT_CLASSIFIER_PARAMS))
net.link("sensor",
"SP",
"UniformLink",
"",
srcOutput="dataOut",
destInput="bottomUpIn")
net.link("SP",
"TM",
"UniformLink",
"",
srcOutput="bottomUpOut",
destInput="activeColumns")
net.link("sensor",
"TM",
"UniformLink",
"",
srcOutput="saccadeOut",
destInput="basalInput")
net.link("TM",
"TP",
"UniformLink",
"",
srcOutput="predictedActiveCells",
destInput="feedforwardInput")
net.link("TP",
"TM",
"UniformLink",
"",
srcOutput="feedForwardOutput",
destInput="apicalInput")
net.link("TP",
"classifier",
"UniformLink",
"",
srcOutput="feedForwardOutput",
destInput="bottomUpIn")
#net.link("TM", "classifier", "UniformLink", "",
# srcOutput="predictedActiveCells", destInput="bottomUpIn")
net.link("sensor",
"classifier",
"UniformLink",
"",
srcOutput="categoryOut",
destInput="categoryIn")
self.net = net
self.networkSensor = self.net.regions["sensor"]
self.networkSP = self.net.regions["SP"]
self.networkTM = self.net.regions["TM"]
self.networkTP = self.net.regions["TP"]
self.networkClassifier = self.net.regions["classifier"]
