#Num iterations 'outerSteps': 10000000, #1000000, 'innerSteps': 50, #300, #Batch size 'batchSize': 128, #Learning rate for optimizer 'learningRate': 1e-3, 'numClasses': 10, 'verifyTrain': False, 'verifyTest': False, #####ISTA PARAMS###### 'VStrideY': 2, 'VStrideX': 2, 'rectify': False, #SLP params 'pooledY': 8, 'pooledX': 8, } #Allocate tensorflow object #This will build the graph tfObj = SLP(params, trainDataObj.inputShape) print "Done init" tfObj.runModel(trainDataObj, testDataObj=testDataObj) print "Done run" tfObj.closeSess()
#Device to run on 'device': '/gpu:0', #Num iterations 'outerSteps': 10000000, #1000000, 'innerSteps': 50, #300, #Batch size 'batchSize': 4, #Learning rate for optimizer 'learningRate': 1e-4, 'numClasses': 10, 'verifyTrain': False, 'verifyTest': False, #####ISTA PARAMS###### 'VStrideY': 2, 'VStrideX': 2, 'rectify': False, } #Allocate tensorflow object #This will build the graph tfObj = SLP(params, trainDataObj.inputShape) print "Done init" tfObj.runModel(trainDataObj, testDataObj = testDataObj, numTest=256) print "Done run" tfObj.closeSess()
'pvpWeightFile': "/home/slundquist/mountData/datasets/cifar/pvp/128/CIFAR_128_W.pvp", #Device to run on 'device': '/gpu:0', #Num iterations 'outerSteps': 10000000, #1000000, 'innerSteps': 50, #300, #Batch size 'batchSize': 128, #Learning rate for optimizer 'learningRate': 1e-4, 'numClasses': 10, 'verifyTrain': False, 'verifyTest': False, #####ISTA PARAMS###### 'VStrideY': 2, 'VStrideX': 2, 'rectify': False, } #Allocate tensorflow object #This will build the graph tfObj = SLP(params, trainDataObj.inputShape) print "Done init" tfObj.runModel(trainDataObj, testDataObj = testDataObj) print "Done run" tfObj.closeSess()