#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()
