def contributionForEachExample(taskEachExample): k = taskEachExample.curK ybar = taskEachExample.curYbar splMode = taskEachExample.splMode setSelected(taskEachExample, splMode, k, ybar, 1.0) (garbageA, garbageB, slackOn) = CommonApp.singleFMVC(taskEachExample.fmvcJob) setSelected(taskEachExample, splMode, k, ybar, 0.0) (garbageA, garbageB, slackOff) = CommonApp.singleFMVC(taskEachExample.fmvcJob) contribTuple = (taskEachExample, (slackOn - slackOff)) return contribTuple
def select(globalSPLVars, w, params):
logging.debug("Fraction %f" % globalSPLVars.fraction)
labels, violations= zip(*CommonApp.accessExamples(params,w, findYAndViolation, None))
cutoffDict = findCutoffs(violations, labels, params.numYLabels,globalSPLVars.fraction)
trueYAndSelections = CommonApp.accessExamples(params, (w, cutoffDict,globalSPLVars.fraction), updateSelectionSPL, None)
for label in range(params.numYLabels):
total = 0
totalOn = 0
for trueYandSelection in trueYAndSelections:
if trueYandSelection[0]==label:
totalOn += trueYandSelection[1]
total+=1
logging.debug("For label %d totalOn %f and total %f" %( label, totalOn, total))
def dumpCurrentLatentVariables(params, lvFile):
idLVpairs = CommonApp.accessExamples(params, None, grabLatentVariables, None)
fh = open(lvFile,'w')
idLVpairs.sort( lambda x,y: int(x[0])-int(y[0]))
for id,LV in idLVpairs:
fh.write("%s %d %d %d %d\n" % (id, LV.x_min, LV.x_max, LV.y_min, LV.y_max))
fh.close()
def reoptimizeW(optState,example): assert(example.params.splParams.splMode == 'CCCP') marginsNew = [] margins = optState.margins FNewtranspose = numpy.asmatrix(numpy.zeros(optState.F.T.shape)) Ftranspose = optState.F.T latents = optState.latents for iteration in range(len(margins)): ybar, hbar = latents[iteration][example.id] contributedMargin = CommonApp.delta(ybar, example.trueY) contributedConstraintGiven = CommonApp.padCanonicalPsi(example.psis()[example.h,:].T, example.trueY, example.params) contributedConstraintHBar = CommonApp.padCanonicalPsi(example.psis()[hbar,:].T, ybar, example.params) FNewtranspose[iteration,:] = (Ftranspose[iteration,:] - (contributedConstraintGiven - contributedConstraintHBar).T) marginsNew.append(margins[iteration]-contributedMargin) FNew = FNewtranspose.T FTF = FNew.T*FNew wNew, objective, gap = SSVM.solveDualQPV2(FTF, FNew,marginsNew,example.params, optState.env,optState.task) return wNew
def main():
try:
params = UserInput.getUserInput('train')
ExampleLoader.loadExamples(params)
CommonApp.setExampleCosts(params)
w = None
if params.initialModelFile:
w = CacheObj.loadObject(params.initialModelFile)
else:
w = CommonApp.PsiObject(params,False)
globalSPLVars = SPLSelector.SPLVar()
if params.splParams.splMode != 'CCCP':
SPLSelector.setupSPL(params)
w = LSSVM.optimize(w, globalSPLVars, params)
CacheObj.cacheObject(params.modelFile,w)
Performance.printStrongAndWeakTrainError(params, w)
except Exception, e :
import traceback
traceback.print_exc(file=sys.stdout)
def impute(optState, params):
logging.debug("Imputing H")
CommonApp.accessExamples(params, optState, imputeSingle, None)
def computeObjective(w, params): objective = 0.5 * (w.T * w)[0,0] (margin, constraint,lvs) = CommonApp.findCuttingPlane(w, params) objective += params.C*(margin - ((w.T * constraint)[0,0])) return (objective, margin, constraint,lvs)
def setupSPL(params): CommonApp.accessExamples(params, None, setupSPLEachExample, None)
