115 lines
3.8 KiB
Python
Executable File
115 lines
3.8 KiB
Python
Executable File
#!/usr/bin/python
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# -*- coding: utf-8 -*-
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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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print(response)
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if response['status'] == 'error':
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raise Exception(response['message'])
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if len(sys.argv) != 9:
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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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lemmatizedSourceFile = sys.argv[3]
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sourceLangId = int(sys.argv[4])
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targetFile = sys.argv[5]
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targetLangId = int(sys.argv[6])
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alignmentsFile = sys.argv[7]
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sourceIdsFile = sys.argv[8]
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sourceFileLength = file_len(sourceFile)
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lemmatizedSourceFileLength = file_len(lemmatizedSourceFile)
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targetFileLength = file_len(targetFile)
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alignmentsFileLength = file_len(alignmentsFile)
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sourceIdsFileLength = file_len(sourceIdsFile)
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if not (sourceFileLength == lemmatizedSourceFileLength and lemmatizedSourceFileLength == targetFileLength and targetFileLength == alignmentsFileLength and alignmentsFileLength == sourceIdsFileLength):
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print("File lengths:")
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print("source file: %d\nlemmatized source file: %d\ntarget file: %d\nalignments file: %d\nsource ids file: %d" % (sourceFileLength, lemmatizedSourceFileLength, targetFileLength, alignmentsFileLength, sourceIdsFileLength))
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raise Exception("files are not of the same length!")
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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': 'addSentences',
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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 source_file, open(lemmatizedSourceFile) as lemmatized_source_file, open(targetFile) as target_file, open(alignmentsFile) as alignments_file, open(sourceIdsFile) as source_ids_file:
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for lineNumber in range(totalExamples):
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sourceSentence = source_file.readline().strip()
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lemmatizedSourceSentence = lemmatized_source_file.readline().strip()
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targetSentence = target_file.readline().strip()
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alignment = json.loads(alignments_file.readline().strip())
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sourceId = int(source_ids_file.readline().strip())
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examples.append([sourceSentence, lemmatizedSourceSentence, targetSentence, alignment, sourceId])
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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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