buildfsa.py
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# -*- coding:utf-8 -*-
'''
Created on 21 paź 2013
@author: mlenart
'''
import sys
import logging
import codecs
import encode
import convertinput
import common
from fsa import FSA
from serializer import VLengthSerializer1, VLengthSerializer2, SimpleSerializer
from optparse import OptionParser
class OutputFormat():
BINARY = 'BINARY'
CPP = 'CPP'
# class InputFormat():
# ENCODED = 'ENCODED'
# POLIMORF = 'POLIMORF'
# PLAIN = 'PLAIN'
class FSAType():
MORPH = 'MORPH'
SPELL = 'SPELL'
class SerializationMethod():
SIMPLE = 'SIMPLE'
V1 = 'V1'
V2 = 'V2'
def _parseOptions():
"""
Parses commandline args
"""
parser = OptionParser()
parser.add_option('-i', '--input-file',
dest='inputFile',
metavar='FILE',
help='path to input file')
parser.add_option('--tagset-file',
dest='tagsetFile',
metavar='FILE',
help='path to the file with tagset')
parser.add_option('-o', '--output-file',
dest='outputFile',
metavar='FILE',
help='path to output file')
# parser.add_option('-t', '--fsa-type',
# dest='fsaType',
# help='result FSA type - MORPH (for morphological analysis) or SPELL (for simple spell checker)')
# parser.add_option('--input-format',
# dest='inputFormat',
# help='input format - ENCODED, POLIMORF or PLAIN')
parser.add_option('--output-format',
dest='outputFormat',
help='output format - BINARY or CPP')
parser.add_option('--use-arrays',
dest='useArrays',
action='store_true',
default=False,
help='store states reachable by 2 transitions in arrays (should speed up recognition, available only when --serialization-method=V1)')
parser.add_option('--serialization-method',
dest='serializationMethod',
help="FSA serialization method: \
SIMPLE - fixed-length transitions, fastest and weakest compression \
V1 - variable-length transitions, compressed labels - strongest compression \
V2 - format similar to the default in Jan Daciuk's fsa package - variable-length transitions, non-compressed labels - good compression, good speed")
parser.add_option('--visualize',
dest='visualize',
action='store_true',
default=False,
help='visualize result')
parser.add_option('--train-file',
dest='trainFile',
help='A text file used for training. Should contain words from some large corpus - one word in each line')
parser.add_option('--debug',
dest='debug',
action='store_true',
default=False,
help='output some debugging info')
parser.add_option('--profile',
dest='profile',
action='store_true',
default=False,
help='show profiling graph (required pycallgraph and graphviz')
opts, args = parser.parse_args()
if None in [opts.inputFile, opts.outputFile, opts.outputFormat, opts.tagsetFile, opts.serializationMethod]:
parser.print_help()
exit(1)
if not opts.outputFormat.upper() in [OutputFormat.BINARY, OutputFormat.CPP]:
logging.error('--output-format must be one of ('+str([OutputFormat.BINARY, OutputFormat.CPP])+')')
parser.print_help()
exit(1)
# if not opts.inputFormat.upper() in [InputFormat.ENCODED, InputFormat.POLIMORF, InputFormat.PLAIN]:
# logging.error('input format must be one of ('+str([InputFormat.ENCODED, InputFormat.POLIMORF, InputFormat.PLAIN])+')')
# parser.print_help()
# exit(1)
# if not opts.fsaType.upper() in [FSAType.MORPH, FSAType.SPELL]:
# logging.error('--fsa-type must be one of ('+str([FSAType.MORPH, FSAType.SPELL])+')')
# parser.print_help()
# exit(1)
# if opts.fsaType == FSAType.MORPH and opts.tagsetFile is None:
# logging.error('must provide tagset file')
# parser.print_help()
# exit(1)
if not opts.serializationMethod.upper() in [SerializationMethod.SIMPLE, SerializationMethod.V1, SerializationMethod.V2]:
logging.error('--serialization-method must be one of ('+str([SerializationMethod.SIMPLE, SerializationMethod.V1, SerializationMethod.V2])+')')
parser.print_help()
exit(1)
# if opts.inputFormat.upper() == FSAType.MORPH \
# and not opts.inputFormat.upper() in [InputFormat.ENCODED, InputFormat.POLIMORF]:
# logging.error('input format for morph analysis FSA must be one of ('+str([InputFormat.ENCODED, InputFormat.POLIMORF])+')')
# parser.print_help()
# exit(1)
# if opts.inputFormat.upper() == FSAType.SPELL \
# and not opts.inputFormat.upper() in [InputFormat.PLAIN]:
# logging.error('input format for simple spelling FSA must be '+InputFormat.PLAIN)
# parser.print_help()
# exit(1)
return opts
def _readPolimorfInput(inputFile, tagset, encoder):
with open(inputFile, 'r') as f:
for entry in convertinput.PolimorfConverter(tagset, encoder, 'utf8').convert(f):
yield entry
def _readPlainInput(inputFile, encoder):
with codecs.open(inputFile, 'r', 'utf8') as f:
for line in sorted(f, key=encoder.word2SortKey):
word = line.strip()
yield word, ''
def _readTrainData(trainFile):
with codecs.open(trainFile, 'r', 'utf8') as f:
for line in f:
yield line.strip()
def _printStats(fsa):
acceptingNum = 0
sinkNum = 0
arrayNum = 0
for s in fsa.dfs():
if s.isAccepting():
acceptingNum += 1
if s.transitionsNum == 0:
sinkNum += 1
if s.serializeAsArray:
arrayNum += 1
logging.info('states num: '+str(fsa.getStatesNum()))
logging.info('transitions num: '+str(fsa.getTransitionsNum()))
logging.info('accepting states num: '+str(acceptingNum))
logging.info('sink states num: '+str(sinkNum))
logging.info('array states num: '+str(arrayNum))
def buildFromPoliMorf(inputFile, tagsetFile):
encoder = encode.MorphEncoder()
tagset = common.Tagset(tagsetFile)
fsa = FSA(encoder, tagset)
inputData = _readPolimorfInput(inputFile, tagset, encoder)
fsa.feed(inputData)
_printStats(fsa)
return fsa
def buildFromPlain(inputFile, tagsetFile):
pass
def main(opts):
if opts.debug:
logging.basicConfig(level=logging.DEBUG)
else:
logging.basicConfig(level=logging.INFO)
fsa = buildFromPoliMorf(opts.inputFile, opts.tagsetFile)
# {
# FSAType.SPELL: buildFromPlain(opts.inputFile),
# FSAType.MORPH: buildFromPoliMorf(opts.inputFile, opts.tagsetFile)
# }[opts.fsaType]
if opts.trainFile:
logging.info('training with '+opts.trainFile+' ...')
fsa.train(_readTrainData(opts.trainFile))
logging.info('done training')
# encoder = {
# FSAType.SPELL: encode.SimpleEncoder(),
# FSAType.MORPH: encode.MorphEncoder()
# }[opts.fsaType]
#
# fsa = FSA(encoder)
#
# inputData = {
# FSAType.MORPH: _readPolimorfInput(opts.inputFile, opts.tagsetFile, encoder),
# FSAType.SPELL: _readPlainInput(opts.inputFile, encoder)
# }[opts.fsaType]
# logging.info('feeding FSA with data ...')
# fsa.feed(inputData)
# if opts.trainFile:
# logging.info('training with '+opts.trainFile+' ...')
# fsa.train(readTrainData(opts.trainFile))
# logging.info('done training')
serializer = {
SerializationMethod.SIMPLE: SimpleSerializer,
SerializationMethod.V1: VLengthSerializer1,
SerializationMethod.V2: VLengthSerializer2,
}[opts.serializationMethod](fsa)
{
OutputFormat.CPP: serializer.serialize2CppFile,
OutputFormat.BINARY: serializer.serialize2BinaryFile
}[opts.outputFormat](opts.outputFile)
logging.info('size: '+str(fsa.initialState.reverseOffset))
if opts.visualize:
from visualizer import Visualizer
Visualizer().visualize(fsa)
if __name__ == '__main__':
import os
print os.getcwd()
opts = _parseOptions()
if opts.profile:
from pycallgraph import PyCallGraph
from pycallgraph.output import GraphvizOutput
with PyCallGraph(output=GraphvizOutput()):
main(opts)
else:
main(opts)