'learningRateBias': 1e-6, #'numClasses': trainDataObj.numClasses, 'numClasses': trainDataObj.numClasses, 'idxToName': trainDataObj.idxToName, 'preTrain': False, 'lossWeight': trainDataObj.lossWeight, 'gtShape': trainDataObj.gtShape, 'gtSparse': False, 'inputScale': 100, 'regWeight': 1e-4, 'resLoad': True, } #Allocate tensorflow object #This will build the graph tfObj = MLPVid(stage2_params, trainDataObj.inputShape) print "Done init" tfObj.runModel(trainDataObj, testDataObj=testDataObj) print "Done run" tfObj.closeSess() stage3_params = { #Base output directory 'outDir': "/home/slundquist/mountData/DeepGAP/", #Inner run directory 'runDir': "/pv_kitti_vid_4x8_boot_3_bin/", 'tfDir': "/tfout", #Save parameters 'ckptDir': "/checkpoints/",
'innerSteps': 100, #300, #Batch size 'batchSize': 16, #Learning rate for optimizer 'learningRate': 1e-4, 'beta1': .9, 'beta2': .999, 'epsilon': 1e-8, 'learningRateBias': 1e-6, #'numClasses': trainDataObj.numClasses, 'numClasses': trainDataObj.numClasses, 'idxToName': trainDataObj.idxToName, 'preTrain': False, 'lossWeight': trainDataObj.lossWeight, 'gtShape': trainDataObj.gtShape, 'gtSparse': False, 'inputScale': 100, 'regWeight': 1e-4, 'resLoad': True, } #Allocate tensorflow object #This will build the graph tfObj = MLPVid(params, trainDataObj.inputShape) print "Done init" tfObj.runModel(trainDataObj, testDataObj=testDataObj) print "Done run" tfObj.closeSess()