112 lines
3.1 KiB
Python
112 lines
3.1 KiB
Python
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#!/usr/bin/python
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# -*- coding: utf-8 -*-
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import unittest
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import json
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import urllib2
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import sys
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import host
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import time
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BUFFER_SIZE = 500
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address = 'http://'+host.concordia_host
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if len(host.concordia_port) > 0:
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address += ':'+host.concordia_port
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def file_len(fname):
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with open(fname) as f:
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for i, l in enumerate(f):
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pass
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return i + 1
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def add_examples(examplesData):
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req = urllib2.Request(address)
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req.add_header('Content-Type', 'application/json')
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response = json.loads(urllib2.urlopen(req, json.dumps(examplesData)).read())
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if response['status'] == 'error':
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raise Exception(response['message'])
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if len(sys.argv) != 7:
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raise Exception("wrong number of arguments")
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name = sys.argv[1]
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sourceFile = sys.argv[2]
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sourceLangId = int(sys.argv[3])
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targetFile = sys.argv[4]
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targetLangId = int(sys.argv[5])
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alignmentsFile = sys.argv[6]
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if (file_len(sourceFile) != file_len(targetFile)):
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raise Exception("source and target files are not of the same length!")
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if (file_len(alignmentsFile) != 3*file_len(sourceFile)):
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raise Exception("alignments file is not exactly 3 times longer than source and target")
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totalExamples = file_len(sourceFile)
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data = {
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'operation': 'addTm',
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'sourceLangId':sourceLangId,
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'targetLangId':targetLangId,
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'name':name,
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'tmLemmatized':True
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}
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req = urllib2.Request(address)
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req.add_header('Content-Type', 'application/json')
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response = json.loads(urllib2.urlopen(req, json.dumps(data)).read())
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print(response)
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tmId = int(response['newTmId'])
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print "Added new tm: %d" % tmId
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data = {
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'operation': 'addAlignedLemmatizedSentences',
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'tmId':tmId
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}
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examples = []
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start = time.time()
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with open(sourceFile) as sf, open(targetFile) as tf, open(alignmentsFile) as af:
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for lineNumber in range(totalExamples):
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sourceSentence = sf.readline().strip()
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targetSentence = tf.readline().strip()
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# skip to lines of the alignments file, these are lemmatized and we need the raw sentences from the source and target files.
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af.readline()
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af.readline()
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alignmentString = af.readline().strip()
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examples.append([sourceSentence, targetSentence, alignmentString])
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if len(examples) >= BUFFER_SIZE:
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data['examples'] = examples
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add_examples(data)
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mark = time.time()
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print "Added %d of %d lemmatized examples. Time elapsed: %.4f s, current speed: %.4f examples/second" % ( (lineNumber+1), totalExamples, mark-start, (lineNumber+1)/(mark-start))
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examples = []
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if len(examples) > 0:
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data['examples'] = examples
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add_examples(data)
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end = time.time()
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print "Added all %d lemmatized sentences. Time elapsed: %.4f s, overall speed: %.4f sentences/second" % ((lineNumber+1), end-start, (lineNumber+1)/(end-start))
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print "Generating index..."
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start = time.time()
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data = {
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'operation': 'refreshIndex',
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'tmId' : tmId
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}
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req = urllib2.Request(address)
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req.add_header('Content-Type', 'application/json')
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urllib2.urlopen(req, json.dumps(data)).read()
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end = time.time()
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print "Index regeneration complete. The operation took %.4f s" % (end - start)
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