# -*- coding: utf-8 -*- """ Created on Thu Feb 20 10:36:01 2014 @author: Huang,Zheng A command line wrapper to use LinearCRF class to Test. """ import argparse import LinearCRF2 if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument("datafile", help="data file for Testing input") parser.add_argument("modelfile", help="the learnt model file to load. ") parser.add_argument("resultfile", help="the output file name.") #parser.add_argument("-s", "--sigma", type=float, # default=1, # help="sigma") args = parser.parse_args() LinearCRF2.crfpredict(args.datafile, args.modelfile, args.resultfile)
if __name__ == '__main__': parser = argparse.ArgumentParser() parser.add_argument("datafile", help="data file for training input") parser.add_argument("templatefile", help="template file for generate feature functions.") parser.add_argument("modelfile", help="the learnt model file. (output)") parser.add_argument("-r", "--regularity", type=int, default=2, choices=[0, 1, 2], help="regularity: 0:none; 1:first order; 2:square.") parser.add_argument("-s", "--sigma", type=float, default=1, help="sigma") parser.add_argument("-m", "--multiproc", type=int, default=1, choices=[0,1], help="multiprocessing: 1:use multiprocessing; 0:only single core.") parser.add_argument("-f", "--fd", type=int, default=1, help="feature reduction: the number of observed x under this value is ignored.") args = parser.parse_args() #print args.sigma LinearCRF2.train(args.datafile,args.templatefile,args.modelfile, regtype=args.regularity,sigma=args.sigma,mp=args.multiproc, fd=args.fd)
choices=[0, 1, 2], help="regularity: 0:none; 1:first order; 2:square.") parser.add_argument("-s", "--sigma", type=float, default=1, help="sigma") parser.add_argument( "-m", "--multiproc", type=int, default=1, choices=[0, 1], help="multiprocessing: 1:use multiprocessing; 0:only single core.") parser.add_argument( "-f", "--fd", type=int, default=1, help= "feature reduction: the number of observed x under this value is ignored." ) args = parser.parse_args() #print args.sigma LinearCRF2.train(args.datafile, args.templatefile, args.modelfile, regtype=args.regularity, sigma=args.sigma, mp=args.multiproc, fd=args.fd)