'displayPeriod': 100,
#Batch size
'batchSize': 4,
#Learning rate for optimizer
'learningRate': 1e-4,
'numClasses': 10,
'epsilon': 1e-8,
'regularizer': 'none',
'regWeight': .3,
#####ISTA PARAMS######
'VStrideY': 2,
'VStrideX': 2,
'patchSizeX': 12,
'patchSizeY': 12,
'numV': 256,
#####New encode parapms#####
'maxPool': True, #Controls max or avg pool
'preTrain': False,
}
#Allocate tensorflow object
#This will build the graph
tfObj = Supervised(params, trainDataObj)
print("Done init")
tfObj.runModel(trainDataObj, testDataObj=testDataObj, numTest=256)
print("Done run")
tfObj.closeSess()
'outerSteps': 500, #1000000,
'innerSteps': 100, #300,
#Batch size
'batchSize': 128,
#Learning rate for optimizer
'learningRate': 1e-4,
'numClasses': 10,
'epsilon': 1e-8,
'regularizer': 'none',
'regWeight': .3,
#####ISTA PARAMS######
'VStrideY': 2,
'VStrideX': 2,
'patchSizeX': 12,
'patchSizeY': 12,
'numV': 128,
#####New encode parapms#####
'maxPool': True, #Controls max or avg pool
}
#Allocate tensorflow object
#This will build the graph
tfObj = Supervised(params, trainDataObj.inputShape)
print("Done init")
tfObj.runModel(trainDataObj, testDataObj=testDataObj)
print("Done run")
tfObj.closeSess()