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executable file 176 lines (146 sloc) 6.13 KB
#!/usr/bin/python3
import os
import os.path
import sys
from subprocess import Popen, PIPE
from argparse import ArgumentParser
from operator import itemgetter
import utils
from myconfig import MyConfig
config = MyConfig()
#change cwd to the libpinyin data directory
libpinyin_dir = config.getToolsDir()
libpinyin_sub_dir = os.path.join(libpinyin_dir, 'data')
os.chdir(libpinyin_sub_dir)
#chdir done
def handleError(error):
sys.exit(error)
def handleOneModel(modelfile, reportfile):
modelfilestatuspath = modelfile + config.getStatusPostfix()
modelfilestatus = utils.load_status(modelfilestatuspath)
if not utils.check_epoch(modelfilestatus, 'Generate'):
raise utils.EpochError('Please generate first.\n')
if utils.check_epoch(modelfilestatus, 'Estimate'):
return
reporthandle = open(reportfile, 'wb')
result_line_prefix = "average lambda:"
avg_lambda = 0.
#begin processing
cmdline = ['../utils/training/estimate_k_mixture_model', \
'--deleted-bigram-file', \
config.getEstimatesModel(), \
'--bigram-file', \
modelfile]
subprocess = Popen(cmdline, shell=False, stdout=PIPE, \
close_fds=True)
for line in subprocess.stdout.readlines():
reporthandle.writelines([line])
#remove trailing '\n'
line = line.decode('utf-8')
line = line.rstrip(os.linesep)
if line.startswith(result_line_prefix):
avg_lambda = float(line[len(result_line_prefix):])
reporthandle.close()
(pid, status) = os.waitpid(subprocess.pid, 0)
if status != 0:
sys.exit('estimate k mixture model returns error.')
#end processing
print('average lambda:', avg_lambda)
modelfilestatus['EstimateScore'] = avg_lambda
utils.sign_epoch(modelfilestatus, 'Estimate')
utils.store_status(modelfilestatuspath, modelfilestatus)
def walkThroughModels(path):
for root, dirs, files in os.walk(path, topdown=True, onerror=handleError):
for onefile in files:
filepath = os.path.join(root, onefile)
if onefile.endswith(config.getModelPostfix()):
subpath = os.path.relpath(filepath, path)
reportfile = filepath + config.getReportPostfix()
print("Processing " + subpath)
handleOneModel(filepath, reportfile)
print("Processed " + subpath)
elif onefile.endswith(config.getStatusPostfix()):
pass
elif onefile.endswith(config.getIndexPostfix()):
pass
elif onefile.endswith(config.getReportPostfix()):
pass
else:
print('Unexpected file:' + filepath)
def gatherModels(path, indexname):
indexfilestatuspath = indexname + config.getStatusPostfix()
indexfilestatus = utils.load_status(indexfilestatuspath)
if utils.check_epoch(indexfilestatuspath, 'Estimate'):
return
#begin processing
indexfile = open(indexname, "w")
for root, dirs, files in os.walk(path, topdown=True, onerror=handleError):
for onefile in files:
filepath = os.path.join(root, onefile)
if onefile.endswith(config.getModelPostfix()):
#append one record to index file
subdir = os.path.relpath(root, path)
statusfilepath = filepath + config.getStatusPostfix()
status = utils.load_status(statusfilepath)
if not (utils.check_epoch(status, 'Estimate') and \
'EstimateScore' in status):
raise utils.EpochError('Unknown Error:\n' + \
'Try re-run estimate.\n')
avg_lambda = status['EstimateScore']
line = subdir + '#' + onefile + '#' + str(avg_lambda)
indexfile.writelines([line, os.linesep])
#record written
elif onefile.endswith(config.getStatusPostfix()):
pass
elif onefile.endswith(config.getIndexPostfix()):
pass
elif onefile.endswith(config.getReportPostfix()):
pass
else:
print('Unexpected file:' + filepath)
indexfile.close()
#end processing
utils.sign_epoch(indexfilestatus, 'Estimate')
utils.store_status(indexfilestatuspath, indexfilestatus)
def sortModels(indexname, sortedindexname):
sortedindexfilestatuspath = sortedindexname + config.getStatusPostfix()
sortedindexfilestatus = utils.load_status(sortedindexfilestatuspath)
if utils.check_epoch(sortedindexfilestatus, 'Estimate'):
return
#begin processing
records = []
indexfile = open(indexname, 'r')
for line in indexfile.readlines():
#remove the trailing '\n'
line = line.rstrip(os.linesep)
(subdir, modelname, score) = line.split('#', 2)
score = float(score)
records.append((subdir, modelname, score))
indexfile.close()
records.sort(key=itemgetter(2), reverse=True)
sortedindexfile = open(sortedindexname, 'w')
for record in records:
(subdir, modelname, score) = record
line = subdir + '#' + modelname + '#' + str(score)
sortedindexfile.writelines([line, os.linesep])
sortedindexfile.close()
#end processing
utils.sign_epoch(sortedindexfilestatus, 'Estimate')
utils.store_status(sortedindexfilestatuspath, sortedindexfilestatus)
if __name__ == '__main__':
parser = ArgumentParser(description='Estimate model candidates.')
parser.add_argument('--modeldir', action='store', \
help='model directory', \
default=config.getModelDir())
args = parser.parse_args()
print(args)
print("estimating")
walkThroughModels(args.modeldir)
print("gathering")
indexname = os.path.join(args.modeldir, config.getEstimateIndex())
gatherModels(args.modeldir, indexname)
print("sorting")
sortedindexname = os.path.join(args.modeldir, \
config.getSortedEstimateIndex())
sortModels(indexname, sortedindexname)
print("done")