SYMBOL INDEX (105 symbols across 15 files)

FILE: MNIST-pytorch/data.py
  function loadMNIST (line 10) | def loadMNIST(opt,path):
  function genPerturbations (line 22) | def genPerturbations(opt):
  function makeBatch (line 56) | def makeBatch(opt,data):
  function evalTest (line 66) | def evalTest(opt,data,geometric,classifier):

FILE: MNIST-pytorch/graph.py
  class FullCNN (line 7) | class FullCNN(torch.nn.Module):
    method __init__ (line 8) | def __init__(self,opt):
    method forward (line 32) | def forward(self,opt,image):
  class CNN (line 40) | class CNN(torch.nn.Module):
    method __init__ (line 41) | def __init__(self,opt):
    method forward (line 61) | def forward(self,opt,image):
  class Identity (line 69) | class Identity(torch.nn.Module):
    method __init__ (line 70) | def __init__(self): super(Identity,self).__init__()
    method forward (line 71) | def forward(self,opt,feat): return [feat]
  class STN (line 74) | class STN(torch.nn.Module):
    method __init__ (line 75) | def __init__(self,opt):
    method forward (line 97) | def forward(self,opt,image):
  class ICSTN (line 109) | class ICSTN(torch.nn.Module):
    method __init__ (line 110) | def __init__(self,opt):
    method forward (line 132) | def forward(self,opt,image,p):
  function initialize (line 149) | def initialize(opt,model,stddev,last0=False):

FILE: MNIST-pytorch/options.py
  function set (line 7) | def set(training):

FILE: MNIST-pytorch/util.py
  function mkdir (line 8) | def mkdir(path):
  function imread (line 10) | def imread(fname):
  function imsave (line 12) | def imsave(fname,array):
  function toRed (line 16) | def toRed(content): return termcolor.colored(content,"red",attrs=["bold"])
  function toGreen (line 17) | def toGreen(content): return termcolor.colored(content,"green",attrs=["b...
  function toBlue (line 18) | def toBlue(content): return termcolor.colored(content,"blue",attrs=["bol...
  function toCyan (line 19) | def toCyan(content): return termcolor.colored(content,"cyan",attrs=["bol...
  function toYellow (line 20) | def toYellow(content): return termcolor.colored(content,"yellow",attrs=[...
  function toMagenta (line 21) | def toMagenta(content): return termcolor.colored(content,"magenta",attrs...
  function restoreModel (line 24) | def restoreModel(opt,geometric,classifier,it):
  function saveModel (line 28) | def saveModel(opt,geometric,classifier,it):
  class Visdom (line 32) | class Visdom():
    method __init__ (line 33) | def __init__(self,opt):
    method tileImages (line 38) | def tileImages(self,opt,images,H,W,HN,WN):
    method trainLoss (line 44) | def trainLoss(self,opt,it,loss):
    method testLoss (line 51) | def testLoss(self,opt,it,loss):
    method meanVar (line 57) | def meanVar(self,opt,mean,var):

FILE: MNIST-pytorch/warp.py
  function fit (line 8) | def fit(Xsrc,Xdst):
  function compose (line 19) | def compose(opt,p,dp):
  function inverse (line 28) | def inverse(opt,p):
  function vec2mtrx (line 35) | def vec2mtrx(opt,p):
  function mtrx2vec (line 61) | def mtrx2vec(opt,pMtrx):
  function transformImage (line 73) | def transformImage(opt,image,pMtrx):

FILE: MNIST-tensorflow/data.py
  function loadMNIST (line 9) | def loadMNIST(fname):
  function genPerturbations (line 31) | def genPerturbations(opt):
  function makeBatch (line 63) | def makeBatch(opt,data,PH):
  function evalTest (line 75) | def evalTest(opt,sess,data,PH,prediction,imagesEval=[]):

FILE: MNIST-tensorflow/graph.py
  function fullCNN (line 7) | def fullCNN(opt,image):
  function CNN (line 41) | def CNN(opt,image):
  function STN (line 62) | def STN(opt,image):
  function ICSTN (line 94) | def ICSTN(opt,image,p):
  function createVariable (line 131) | def createVariable(opt,weightShape,biasShape=None,stddev=None):

FILE: MNIST-tensorflow/options.py
  function set (line 6) | def set(training):

FILE: MNIST-tensorflow/util.py
  function mkdir (line 7) | def mkdir(path):
  function imread (line 9) | def imread(fname):
  function imsave (line 11) | def imsave(fname,array):
  function toRed (line 15) | def toRed(content): return termcolor.colored(content,"red",attrs=["bold"])
  function toGreen (line 16) | def toGreen(content): return termcolor.colored(content,"green",attrs=["b...
  function toBlue (line 17) | def toBlue(content): return termcolor.colored(content,"blue",attrs=["bol...
  function toCyan (line 18) | def toCyan(content): return termcolor.colored(content,"cyan",attrs=["bol...
  function toYellow (line 19) | def toYellow(content): return termcolor.colored(content,"yellow",attrs=[...
  function toMagenta (line 20) | def toMagenta(content): return termcolor.colored(content,"magenta",attrs...
  function imageSummary (line 23) | def imageSummary(opt,image,tag,H,W):
  function imageSummaryMeanVar (line 34) | def imageSummaryMeanVar(opt,image,tag,H,W):
  function setOptimizer (line 44) | def setOptimizer(opt,loss,lrGP,lrC):
  function restoreModel (line 58) | def restoreModel(opt,sess,saver,it):
  function saveModel (line 61) | def saveModel(opt,sess,saver,it):

FILE: MNIST-tensorflow/warp.py
  function fit (line 6) | def fit(Xsrc,Xdst):
  function compose (line 17) | def compose(opt,p,dp):
  function inverse (line 27) | def inverse(opt,p):
  function vec2mtrx (line 35) | def vec2mtrx(opt,p):
  function mtrx2vec (line 54) | def mtrx2vec(opt,pMtrx):
  function transformImage (line 67) | def transformImage(opt,image,pMtrx):

FILE: traffic-sign-tensorflow/data.py
  function loadGTSRB (line 11) | def loadGTSRB(opt,fname):
  function genPerturbations (line 72) | def genPerturbations(opt):
  function makeBatch (line 104) | def makeBatch(opt,data,PH):
  function evalTest (line 116) | def evalTest(opt,sess,data,PH,prediction,imagesEval=[]):

FILE: traffic-sign-tensorflow/graph.py
  function fullCNN (line 7) | def fullCNN(opt,image):
  function CNN (line 38) | def CNN(opt,image):
  function STN (line 63) | def STN(opt,image):
  function ICSTN (line 91) | def ICSTN(opt,imageFull,p):
  function createVariable (line 124) | def createVariable(opt,weightShape,biasShape=None,stddev=None):

FILE: traffic-sign-tensorflow/options.py
  function set (line 6) | def set(training):

FILE: traffic-sign-tensorflow/util.py
  function mkdir (line 7) | def mkdir(path):
  function imread (line 9) | def imread(fname):
  function imsave (line 11) | def imsave(fname,array):
  function toRed (line 15) | def toRed(content): return termcolor.colored(content,"red",attrs=["bold"])
  function toGreen (line 16) | def toGreen(content): return termcolor.colored(content,"green",attrs=["b...
  function toBlue (line 17) | def toBlue(content): return termcolor.colored(content,"blue",attrs=["bol...
  function toCyan (line 18) | def toCyan(content): return termcolor.colored(content,"cyan",attrs=["bol...
  function toYellow (line 19) | def toYellow(content): return termcolor.colored(content,"yellow",attrs=[...
  function toMagenta (line 20) | def toMagenta(content): return termcolor.colored(content,"magenta",attrs...
  function imageSummary (line 23) | def imageSummary(opt,image,tag,H,W):
  function imageSummaryMeanVar (line 34) | def imageSummaryMeanVar(opt,image,tag,H,W):
  function setOptimizer (line 45) | def setOptimizer(opt,loss,lrGP,lrC):
  function restoreModel (line 59) | def restoreModel(opt,sess,saver,it):
  function saveModel (line 62) | def saveModel(opt,sess,saver,it):

FILE: traffic-sign-tensorflow/warp.py
  function fit (line 6) | def fit(Xsrc,Xdst):
  function compose (line 17) | def compose(opt,p,dp):
  function inverse (line 27) | def inverse(opt,p):
  function vec2mtrx (line 35) | def vec2mtrx(opt,p):
  function mtrx2vec (line 54) | def mtrx2vec(opt,pMtrx):
  function transformImage (line 67) | def transformImage(opt,image,pMtrx):
  function transformCropImage (line 110) | def transformCropImage(opt,imageFull,pMtrx):