def process(zh, en, zh_vocab, en_vocab, writer_name):
assert len(zh) == len(en), 'bad data set'
writer = tf.python_io.TFRecordWriter(writer_name)
for i in range(len(zh)):
# print(i)
zh_line = sentence2int(chinese_parse(zh[i].strip()), zh_vocab)
en_line = sentence2int(english_parse(en[i].strip()), en_vocab)
example = _convert_to_example(zh_line, en_line)
writer.write(example.SerializeToString())
def build_partial_vocab_dict(partial_lines, filename):
vocab_count = {}
maxLen = 0
if filename.split('.')[-2] == 'zh':
parse = lambda x: chinese_parse(x)
else:
parse = lambda x: english_parse(x)
# parse = lambda x : pynlpir.segment(x,pos_tagging=False)
for i, line in enumerate(partial_lines):
try:
line = parse(line)
except:
print('unicode error line ' + str(i + 1))
if len(line) > maxLen:
maxLen = len(line)
for word in line:
if word not in vocab_count:
# print(word)
vocab_count[word] = 1
else:
vocab_count[word] += 1
return vocab_count, maxLen
def zh_process(zh, num_threads, thread_id, i, zh_vocab):
return sentence2int(chinese_parse(zh[i * num_threads + thread_id].strip()), zh_vocab)