concordia-server/tests/addFastAlignedTM.py

115 lines
3.8 KiB
Python
Executable File

#!/usr/bin/python
# -*- coding: utf-8 -*-
import json
import urllib2
import sys
import host
import time
BUFFER_SIZE = 500
address = 'http://'+host.concordia_host
if len(host.concordia_port) > 0:
address += ':'+host.concordia_port
def file_len(fname):
with open(fname) as f:
for i, l in enumerate(f):
pass
return i + 1
def add_examples(examplesData):
req = urllib2.Request(address)
req.add_header('Content-Type', 'application/json')
response = json.loads(urllib2.urlopen(req, json.dumps(examplesData)).read())
print(response)
if response['status'] == 'error':
raise Exception(response['message'])
if len(sys.argv) != 9:
raise Exception("wrong number of arguments")
name = sys.argv[1]
sourceFile = sys.argv[2]
lemmatizedSourceFile = sys.argv[3]
sourceLangId = int(sys.argv[4])
targetFile = sys.argv[5]
targetLangId = int(sys.argv[6])
alignmentsFile = sys.argv[7]
sourceIdsFile = sys.argv[8]
sourceFileLength = file_len(sourceFile)
lemmatizedSourceFileLength = file_len(lemmatizedSourceFile)
targetFileLength = file_len(targetFile)
alignmentsFileLength = file_len(alignmentsFile)
sourceIdsFileLength = file_len(sourceIdsFile)
if not (sourceFileLength == lemmatizedSourceFileLength and lemmatizedSourceFileLength == targetFileLength and targetFileLength == alignmentsFileLength and alignmentsFileLength == sourceIdsFileLength):
print("File lengths:")
print("source file: %d\nlemmatized source file: %d\ntarget file: %d\nalignments file: %d\nsource ids file: %d" % (sourceFileLength, lemmatizedSourceFileLength, targetFileLength, alignmentsFileLength, sourceIdsFileLength))
raise Exception("files are not of the same length!")
totalExamples = file_len(sourceFile)
data = {
'operation': 'addTm',
'sourceLangId':sourceLangId,
'targetLangId':targetLangId,
'name':name,
'tmLemmatized':True
}
req = urllib2.Request(address)
req.add_header('Content-Type', 'application/json')
response = json.loads(urllib2.urlopen(req, json.dumps(data)).read())
print(response)
tmId = int(response['newTmId'])
print "Added new tm: %d" % tmId
data = {
'operation': 'addSentences',
'tmId':tmId
}
examples = []
start = time.time()
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:
for lineNumber in range(totalExamples):
sourceSentence = source_file.readline().strip()
lemmatizedSourceSentence = lemmatized_source_file.readline().strip()
targetSentence = target_file.readline().strip()
alignment = json.loads(alignments_file.readline().strip())
sourceId = int(source_ids_file.readline().strip())
examples.append([sourceSentence, lemmatizedSourceSentence, targetSentence, alignment, sourceId])
if len(examples) >= BUFFER_SIZE:
data['examples'] = examples
add_examples(data)
mark = time.time()
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))
examples = []
if len(examples) > 0:
data['examples'] = examples
add_examples(data)
end = time.time()
print "Added all %d lemmatized sentences. Time elapsed: %.4f s, overall speed: %.4f sentences/second" % ((lineNumber+1), end-start, (lineNumber+1)/(end-start))
print "Generating index..."
start = time.time()
data = {
'operation': 'refreshIndex',
'tmId' : tmId
}
req = urllib2.Request(address)
req.add_header('Content-Type', 'application/json')
urllib2.urlopen(req, json.dumps(data)).read()
end = time.time()
print "Index regeneration complete. The operation took %.4f s" % (end - start)