def _seed(self, seed=-1):
"""
Initialize the random seed
"""
if seed != -1:
self.random = NupicRandom(seed)
else:
self.random = NupicRandom()
def read(cls, proto):
encoder = object.__new__(cls)
encoder.resolution = proto.resolution
encoder.w = proto.w
encoder.n = proto.n
encoder.name = proto.name
if proto.offset.which() == "none":
encoder._offset = None
else:
encoder._offset = proto.offset.value
encoder.random = NupicRandom()
encoder.random.read(proto.random)
encoder.resolution = proto.resolution
encoder.verbosity = proto.verbosity
encoder.minIndex = proto.minIndex
encoder.maxIndex = proto.maxIndex
encoder.encoders = None
encoder._maxBuckets = INITIAL_BUCKETS
encoder._maxOverlap = proto.maxOverlap or 0
encoder.numTries = proto.numTries or 0
encoder.bucketMap = {
x.key: numpy.array(x.value, dtype=numpy.uint32)
for x in proto.bucketMap
}
return encoder
def read(cls, proto):
encoder = object.__new__(cls)
encoder.n = proto.n
encoder.w = proto.w
encoder.random = NupicRandom()
encoder.random.read(proto.random)
encoder.verbosity = proto.verbosity
encoder.name = proto.name
encoder.description = [(proto.name, 0)]
encoder.categories = list(proto.categories)
encoder.sdrs = numpy.array(proto.sdrs, dtype=numpy.uint8)
encoder.categoryToIndex = {
category: index
for index, category in enumerate(encoder.categories)
}
encoder.ncategories = len(encoder.categories)
encoder._learningEnabled = proto.learningEnabled
encoder._initOverlap()
encoder._topDownMappingM = None
encoder._topDownValues = None
encoder.encoders = None
return encoder
def __setstate__(self, state):
self.__dict__.update(state)
# Initialize self.random as an instance of NupicRandom derived from the
# previous numpy random state
randomState = state["random"]
if isinstance(randomState, numpy.random.mtrand.RandomState):
self.random = NupicRandom(randomState.randint(sys.maxsize))
def read(cls, proto):
encoder = object.__new__(cls)
encoder.w = proto.w
encoder.n = proto.n
encoder.name = proto.name
encoder.random = NupicRandom()
encoder.random.read(proto.random)
encoder.verbosity = proto.verbosity
encoder.encoders = None
encoder.bucketMap = {
x.key: numpy.array(x.value, dtype=numpy.uint32)
for x in proto.bucketMap
}
return encoder
def convertSP(self, pySp, newSeed):
columnDim = pySp._columnDimensions
inputDim = pySp._inputDimensions
numInputs = pySp.getNumInputs()
numColumns = pySp.getNumColumns()
cppSp = CPPSpatialPooler(inputDim, columnDim)
cppSp.setPotentialRadius(pySp.getPotentialRadius())
cppSp.setPotentialPct(pySp.getPotentialPct())
cppSp.setGlobalInhibition(pySp.getGlobalInhibition())
numActiveColumnsPerInhArea = pySp.getNumActiveColumnsPerInhArea()
localAreaDensity = pySp.getLocalAreaDensity()
if (numActiveColumnsPerInhArea > 0):
cppSp.setNumActiveColumnsPerInhArea(numActiveColumnsPerInhArea)
else:
cppSp.setLocalAreaDensity(localAreaDensity)
cppSp.setStimulusThreshold(pySp.getStimulusThreshold())
cppSp.setInhibitionRadius(pySp.getInhibitionRadius())
cppSp.setDutyCyclePeriod(pySp.getDutyCyclePeriod())
cppSp.setMaxBoost(pySp.getMaxBoost())
cppSp.setIterationNum(pySp.getIterationNum())
cppSp.setIterationLearnNum(pySp.getIterationLearnNum())
cppSp.setSpVerbosity(pySp.getSpVerbosity())
cppSp.setUpdatePeriod(pySp.getUpdatePeriod())
cppSp.setSynPermTrimThreshold(pySp.getSynPermTrimThreshold())
cppSp.setSynPermActiveInc(pySp.getSynPermActiveInc())
cppSp.setSynPermInactiveDec(pySp.getSynPermInactiveDec())
cppSp.setSynPermBelowStimulusInc(pySp.getSynPermBelowStimulusInc())
cppSp.setSynPermConnected(pySp.getSynPermConnected())
cppSp.setMinPctOverlapDutyCycles(pySp.getMinPctOverlapDutyCycles())
cppSp.setMinPctActiveDutyCycles(pySp.getMinPctActiveDutyCycles())
boostFactors = numpy.zeros(numColumns).astype(realType)
pySp.getBoostFactors(boostFactors)
cppSp.setBoostFactors(boostFactors)
overlapDuty = numpy.zeros(numColumns).astype(realType)
pySp.getOverlapDutyCycles(overlapDuty)
cppSp.setOverlapDutyCycles(overlapDuty)
activeDuty = numpy.zeros(numColumns).astype(realType)
pySp.getActiveDutyCycles(activeDuty)
cppSp.setActiveDutyCycles(activeDuty)
minOverlapDuty = numpy.zeros(numColumns).astype(realType)
pySp.getMinOverlapDutyCycles(minOverlapDuty)
cppSp.setMinOverlapDutyCycles(minOverlapDuty)
minActiveDuty = numpy.zeros(numColumns).astype(realType)
pySp.getMinActiveDutyCycles(minActiveDuty)
cppSp.setMinActiveDutyCycles(minActiveDuty)
for i in xrange(numColumns):
potential = numpy.zeros(numInputs).astype(uintType)
pySp.getPotential(i, potential)
cppSp.setPotential(i, potential)
perm = numpy.zeros(numInputs).astype(realType)
pySp.getPermanence(i, perm)
cppSp.setPermanence(i, perm)
pySp._random = NupicRandom(newSeed)
cppSp.seed_(newSeed)
return cppSp
def read(cls, proto):
"""
Override the Spatial pooler deserialization for union pooler.
"""
instance = cls.__new__(cls)
# Spatial Pooler (copied)
VERSION = 3
EPSILON_ROUND = 5
instance._random = NupicRandom()
instance._random.read(proto.random)
instance._numInputs = proto.numInputs
instance._numColumns = proto.numColumns
instance._columnDimensions = numpy.array(proto.columnDimensions)
instance._inputDimensions = numpy.array(proto.inputDimensions)
instance._potentialRadius = proto.potentialRadius
instance._potentialPct = round(proto.potentialPct,
EPSILON_ROUND)
instance._inhibitionRadius = proto.inhibitionRadius
instance._globalInhibition = proto.globalInhibition
instance._numActiveColumnsPerInhArea = proto.numActiveColumnsPerInhArea
instance._localAreaDensity = proto.localAreaDensity
instance._stimulusThreshold = proto.stimulusThreshold
instance._synPermInactiveDec = round(proto.synPermInactiveDec,
EPSILON_ROUND)
instance._synPermActiveInc = round(proto.synPermActiveInc, EPSILON_ROUND)
instance._synPermBelowStimulusInc = round(proto.synPermBelowStimulusInc,
EPSILON_ROUND)
instance._synPermConnected = round(proto.synPermConnected,
EPSILON_ROUND)
instance._minPctOverlapDutyCycles = round(proto.minPctOverlapDutyCycles,
EPSILON_ROUND)
instance._dutyCyclePeriod = proto.dutyCyclePeriod
instance._boostStrength = proto.boostStrength
instance._wrapAround = proto.wrapAround
instance._spVerbosity = proto.spVerbosity
instance._synPermMin = proto.synPermMin
instance._synPermMax = proto.synPermMax
instance._synPermTrimThreshold = round(proto.synPermTrimThreshold,
EPSILON_ROUND)
# TODO: These two overlaps attributes aren't currently saved.
instance._overlaps = numpy.zeros(numColumns, dtype=realDType)
instance._boostedOverlaps = numpy.zeros(numColumns, dtype=realDType)
instance._updatePeriod = proto.updatePeriod
instance._version = VERSION
instance._iterationNum = proto.iterationNum
instance._iterationLearnNum = proto.iterationLearnNum
instance._potentialPools = BinaryCorticalColumns(numInputs)
instance._potentialPools.resize(numColumns, numInputs)
instance._potentialPools.read(proto.potentialPools)
instance._permanences = CorticalColumns(numColumns, numInputs)
instance._permanences.read(proto.permanences)
# Initialize ephemerals and make sure they get updated
instance._connectedCounts = numpy.zeros(numColumns, dtype=realDType)
instance._connectedSynapses = BinaryCorticalColumns(numInputs)
instance._connectedSynapses.resize(numColumns, numInputs)
for columnIndex in xrange(proto.numColumns):
instance._updatePermanencesForColumn(
instance._permanences[columnIndex], columnIndex, False
)
instance._tieBreaker = numpy.array(proto.tieBreaker, dtype=realDType)
instance._overlapDutyCycles = numpy.array(proto.overlapDutyCycles,
dtype=realDType)
instance._activeDutyCycles = numpy.array(proto.activeDutyCycles,
dtype=realDType)
instance._minOverlapDutyCycles = numpy.array(proto.minOverlapDutyCycles,
dtype=realDType)
instance._boostFactors = numpy.array(proto.boostFactors, dtype=realDType)
# Union Temporal Pooler
instance._activeOverlapWeight = proto.activeOverlapWeight
instance._predictedActiveOverlapWeight = proto.predictedActiveOverlapWeight
instance._maxUnionActivity = proto.maxUnionActivity
instance._synPermPredActiveInc = proto.synPermPredActiveInc
instance._synPermPreviousPredActiveInc = proto.synPermPreviousPredActiveInc
instance._historyLength = proto.historyLength
instance._minHistory = proto.minHistory
instance._decayFunctionType = proto.exciteFunctionType
instance._decayFunctionType = proto.decayFunctionType
instance._decayTimeConst = proto.decayTimeConst
instance._decayLinearConst = proto.decayLinearConst
instance._initFunctions();
instance._maxUnionCells = proto.maxUnionCells
instance._poolingActivation = numpy.array(proto.poolingActivation, dtype=REAL_DTYPE)
instance._poolingActivation_tieBreaker = numpy.array(proto.poolingActivationTieBreaker, dtype=REAL_DTYPE)
instance._poolingTimer = numpy.array(proto.poolingTimer, dtype=REAL_DTYPE)
instance._poolingActivationInitLevel = numpy.array(proto.poolingActivationInitLevel, dtype=REAL_DTYPE)
instance._poolingActivationlowerBound = proto.poolingActivationLowerBound
instance._unionSDR = numpy.array(proto.unionSDR, dtype='uint32')
instance._activeCells = numpy.array(proto.activeCells, dtype='uint32')
instance._preActiveInput = numpy.array(proto.preActiveInput, dtype=REAL_DTYPE)
# load matrix
instance._prePredictedActiveInput = [[] for _ in xrange(len(proto.prePredictedActiveInput))]
for row, rowProto in zip(instance._prePredictedActiveInput, proto.prePredictedActiveInput):
row = numpy.array(rowProto, dtype=REAL_DTYPE)
return instance
