def deserialize(self,
serialObjectDict=None,
fileName=None,
useCompression=False):
import daal
if fileName != None and serialObjectDict == None:
bufferArray = np.load(fileName)
buffArrObjName = open(fileName.rsplit(".", 1)[0] + ".txt",
"r").read()
elif fileName == None and any(serialObjectDict):
bufferArray = serialObjectDict["Array Object"]
buffArrObjName = serialObjectDict["Object Information"]
else:
warnings.warn(
'Expecting "bufferArray" or "fileName" argument, NOT both')
raise SystemExit
if useCompression == True:
bufferArray = MultiSVM.decompress(self, bufferArray)
dataArch = OutputDataArchive(bufferArray)
try:
deSerialObj = eval(buffArrObjName)
except AttributeError:
deSerialObj = HomogenNumericTable()
deSerialObj.deserialize(dataArch)
return deSerialObj
def deserializeNumericTable(buffer):
# Create a data archive to deserialize the numeric table
dataArch = OutputDataArchive(buffer)
# Create a numeric table object
dataTable = HomogenNumericTable()
# Deserialize the numeric table from the data archive
dataTable.deserialize(dataArch)
return dataTable
def broadcastWeightsAndBiasesToNodes(wb):
wbBuffer = None
# Serialize weights and biases on the root node
if rankId == MPI_ROOT:
if not wb:
# Weights and biases table should be valid and not NULL on master
return HomogenNumericTable()
wbDataArch = InputDataArchive()
wb.serialize(wbDataArch)
wbBuffer = np.zeros(wbDataArch.getSizeOfArchive(), dtype=np.uint8)
wbDataArch.copyArchiveToArray(wbBuffer)
# Broadcast the serialized weights and biases
wbBuffer = comm.bcast(wbBuffer)
# Deserialize weights and biases
wbDataArchLocal = OutputDataArchive(wbBuffer)
wbLocal = HomogenNumericTable(ntype=np.float32)
wbLocal.deserialize(wbDataArchLocal)
return wbLocal