stress_asignment/sloleks_accentuation.py

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2018-03-21 10:35:05 +00:00
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
import numpy as np
from keras.models import load_model
import sys
from prepare_data import *
np.random.seed(7)
data = Data('l', shuffle_all_inputs=False)
content = data._read_content('data/SlovarIJS_BESEDE_utf8.lex')
dictionary, max_word, max_num_vowels, vowels, accented_vowels = data._create_dict(content)
feature_dictionary = data._create_slovene_feature_dictionary()
syllable_dictionary = data._create_syllables_dictionary(content, vowels)
accented_vowels = ['ŕ', 'á', 'ä', 'é', 'ë', 'ě', 'í', 'î', 'ó', 'ô', 'ö', 'ú', 'ü']
letter_location_model, syllable_location_model, syllabled_letters_location_model = data.load_location_models(
'cnn/word_accetuation/cnn_dictionary/v3_10/20_test_epoch.h5',
'cnn/word_accetuation/syllables/v2_4/20_test_epoch.h5',
'cnn/word_accetuation/syllabled_letters/v2_5_3/20_test_epoch.h5')
letter_type_model, syllable_type_model, syllabled_letter_type_model = data.load_type_models(
'cnn/accent_classification/letters/v2_1/20_test_epoch.h5',
'cnn/accent_classification/syllables/v1_0/20_test_epoch.h5',
'cnn/accent_classification/syllabled_letters/v1_0/20_test_epoch.h5')
from lxml import etree
def xml_words_generator(xml_path):
for event, element in etree.iterparse(xml_path, tag="LexicalEntry", encoding="UTF-8"):
words = []
for child in element:
if child.tag == 'WordForm':
msd = None
word = None
for wf in child:
if 'att' in wf.attrib and wf.attrib['att'] == 'msd':
msd = wf.attrib['val']
elif wf.tag == 'FormRepresentation':
for form_rep in wf:
if form_rep.attrib['att'] == 'zapis_oblike':
word = form_rep.attrib['val']
# if msd is not None and word is not None:
# pass
# else:
# print('NOOOOO')
words.append([word, '', msd, word])
yield words
gen = xml_words_generator('data/Sloleks_v1.2.xml')
# Words proccesed: 650250
# Word indeks: 50023
# Word number: 50023
from lxml import etree
import time
gen = xml_words_generator('data/Sloleks_v1.2.xml')
word_glob_num = 0
word_limit = 0
iter_num = 50000
word_index = 0
start_timer = time.time()
iter_index = 0
words = []
lexical_entries_load_number = 0
lexical_entries_save_number = 0
# INSIDE
word_glob_num = 1500686
word_limit = 50000
iter_index = 30
done_lexical_entries = 33522
import gc
with open("data/new_sloleks/new_sloleks.xml", "ab") as myfile:
myfile2 = open('data/new_sloleks/p' + str(iter_index) + '.xml', 'ab')
for event, element in etree.iterparse('data/Sloleks_v1.2.xml', tag="LexicalEntry", encoding="UTF-8", remove_blank_text=True):
# LOAD NEW WORDS AND ACCENTUATE THEM
# print("HERE")
if lexical_entries_save_number < done_lexical_entries:
g = next(gen)
# print(lexical_entries_save_number)
lexical_entries_save_number += 1
lexical_entries_load_number += 1
print(lexical_entries_save_number)
del g
gc.collect()
continue
if word_glob_num >= word_limit:
myfile2.close()
myfile2 = open('data/new_sloleks/p' + str(iter_index) + '.xml', 'ab')
iter_index += 1
print("Words proccesed: " + str(word_glob_num))
print("Word indeks: " + str(word_index))
print("Word number: " + str(len(words)))
print("lexical_entries_load_number: " + str(lexical_entries_load_number))
print("lexical_entries_save_number: " + str(lexical_entries_save_number))
end_timer = time.time()
print("Elapsed time: " + "{0:.2f}".format((end_timer - start_timer) / 60.0) + " minutes")
word_index = 0
words = []
while len(words) < iter_num:
try:
words.extend(next(gen))
lexical_entries_load_number += 1
except:
break
# if word_glob_num > 1:
# break
data = Data('l', shuffle_all_inputs=False)
location_accented_words, accented_words = data.accentuate_word(words, letter_location_model, syllable_location_model,
syllabled_letters_location_model,
letter_type_model, syllable_type_model, syllabled_letter_type_model,
dictionary, max_word, max_num_vowels, vowels, accented_vowels,
feature_dictionary, syllable_dictionary)
word_limit += len(words)
# READ DATA
for child in element:
if child.tag == 'WordForm':
msd = None
word = None
for wf in child:
if wf.tag == 'FormRepresentation':
new_element = etree.Element('feat')
new_element.attrib['att'] = 'naglasna_mesta_oblike'
new_element.attrib['val'] = location_accented_words[word_index]
wf.append(new_element)
new_element = etree.Element('feat')
new_element.attrib['att'] = 'naglašena_oblika'
new_element.attrib['val'] = accented_words[word_index]
wf.append(new_element)
word_glob_num += 1
word_index += 1
# print(etree.tostring(element, encoding="UTF-8"))
myfile2.write(etree.tostring(element, encoding="UTF-8", pretty_print=True))
myfile.write(etree.tostring(element, encoding="UTF-8", pretty_print=True))
element.clear()
lexical_entries_save_number += 1