def loadEngine(engineType, coreType, modelFileName):
core = createMLEngineCore(coreType, 0)
est = None
if coreType <= 2:
print "load non-dnn model"
est = loadSklearnModel(modelFileName)
else:
est = loadDNNModel(modelFileName)
core.loadEstimator(est)
func = EngineSwitcher.get(engineType, "No such an engine")
return (func(core), core, est)
def loadAModel(self, modelFile):
model = loadSklearnModel(modelFile)
self.prodcutModels.append(model)
print model
return
def loadModel(self, ect, mfn):
if ect <= 2:
self.estimator = loadSklearnModel(mfn)
else:
self.loadDNNModel(mfn)
return
def loadAModel(self, modelFile):
self.model = loadSklearnModel(modelFile)
print self.model
return
def loadModel(self, mfn):
self.estimator = loadSklearnModel(mfn)
return