提交 06915d0a 编写于 作者: Q qiaolongfei

add wmt14_util.py and a small dataset on bos for test

上级 f6f444ff
......@@ -25,7 +25,8 @@ __all__ = ['train', 'test', 'build_dict']
URL_DEV_TEST = 'http://www-lium.univ-lemans.fr/~schwenk/cslm_joint_paper/data/dev+test.tgz'
MD5_DEV_TEST = '7d7897317ddd8ba0ae5c5fa7248d3ff5'
URL_TRAIN = 'http://localhost:8989/wmt14.tgz'
# this is a small set of data for test. The original data is too large and will be add later.
URL_TRAIN = 'http://paddlepaddle.bj.bcebos.com/demo/wmt_shrinked_data/wmt14.tgz'
MD5_TRAIN = '7373473f86016f1f48037c9c340a2d5b'
START = "<s>"
......
# Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
from paddle.utils.preprocess_util import save_list, DatasetCreater
class SeqToSeqDatasetCreater(DatasetCreater):
"""
A class to process data for sequence to sequence application.
"""
def __init__(self, data_path, output_path):
"""
data_path: the path to store the train data, test data and gen data
output_path: the path to store the processed dataset
"""
DatasetCreater.__init__(self, data_path)
self.gen_dir_name = 'gen'
self.gen_list_name = 'gen.list'
self.output_path = output_path
def concat_file(self, file_path, file1, file2, output_path, output):
"""
Concat file1 and file2 to be one output file
The i-th line of output = i-th line of file1 + '\t' + i-th line of file2
file_path: the path to store file1 and file2
output_path: the path to store output file
"""
file1 = os.path.join(file_path, file1)
file2 = os.path.join(file_path, file2)
output = os.path.join(output_path, output)
if not os.path.exists(output):
os.system('paste ' + file1 + ' ' + file2 + ' > ' + output)
def cat_file(self, dir_path, suffix, output_path, output):
"""
Cat all the files in dir_path with suffix to be one output file
dir_path: the base directory to store input file
suffix: suffix of file name
output_path: the path to store output file
"""
cmd = 'cat '
file_list = os.listdir(dir_path)
file_list.sort()
for file in file_list:
if file.endswith(suffix):
cmd += os.path.join(dir_path, file) + ' '
output = os.path.join(output_path, output)
if not os.path.exists(output):
os.system(cmd + '> ' + output)
def build_dict(self, file_path, dict_path, dict_size=-1):
"""
Create the dictionary for the file, Note that
1. Valid characters include all printable characters
2. There is distinction between uppercase and lowercase letters
3. There is 3 special token:
<s>: the start of a sequence
<e>: the end of a sequence
<unk>: a word not included in dictionary
file_path: the path to store file
dict_path: the path to store dictionary
dict_size: word count of dictionary
if is -1, dictionary will contains all the words in file
"""
if not os.path.exists(dict_path):
dictory = dict()
with open(file_path, "r") as fdata:
for line in fdata:
line = line.split('\t')
for line_split in line:
words = line_split.strip().split()
for word in words:
if word not in dictory:
dictory[word] = 1
else:
dictory[word] += 1
output = open(dict_path, "w+")
output.write('<s>\n<e>\n<unk>\n')
count = 3
for key, value in sorted(
dictory.items(), key=lambda d: d[1], reverse=True):
output.write(key + "\n")
count += 1
if count == dict_size:
break
self.dict_size = count
def create_dataset(self,
dict_size=-1,
mergeDict=False,
suffixes=['.src', '.trg']):
"""
Create seqToseq dataset
"""
# dataset_list and dir_list has one-to-one relationship
train_dataset = os.path.join(self.data_path, self.train_dir_name)
test_dataset = os.path.join(self.data_path, self.test_dir_name)
gen_dataset = os.path.join(self.data_path, self.gen_dir_name)
dataset_list = [train_dataset, test_dataset, gen_dataset]
train_dir = os.path.join(self.output_path, self.train_dir_name)
test_dir = os.path.join(self.output_path, self.test_dir_name)
gen_dir = os.path.join(self.output_path, self.gen_dir_name)
dir_list = [train_dir, test_dir, gen_dir]
# create directory
for dir in dir_list:
if not os.path.exists(dir):
os.makedirs(dir)
# checkout dataset should be parallel corpora
suffix_len = len(suffixes[0])
for dataset in dataset_list:
file_list = os.listdir(dataset)
if len(file_list) % 2 == 1:
raise RuntimeError("dataset should be parallel corpora")
file_list.sort()
for i in range(0, len(file_list), 2):
if file_list[i][:-suffix_len] != file_list[i + 1][:-suffix_len]:
raise RuntimeError(
"source and target file name should be equal")
# cat all the files with the same suffix in dataset
for suffix in suffixes:
for dataset in dataset_list:
outname = os.path.basename(dataset) + suffix
self.cat_file(dataset, suffix, dataset, outname)
# concat parallel corpora and create file.list
print 'concat parallel corpora for dataset'
id = 0
list = ['train.list', 'test.list', 'gen.list']
for dataset in dataset_list:
outname = os.path.basename(dataset)
self.concat_file(dataset, outname + suffixes[0],
outname + suffixes[1], dir_list[id], outname)
save_list([os.path.join(dir_list[id], outname)],
os.path.join(self.output_path, list[id]))
id += 1
# build dictionary for train data
dict = ['src.dict', 'trg.dict']
dict_path = [
os.path.join(self.output_path, dict[0]),
os.path.join(self.output_path, dict[1])
]
if mergeDict:
outname = os.path.join(train_dir, train_dataset.split('/')[-1])
print 'build src dictionary for train data'
self.build_dict(outname, dict_path[0], dict_size)
print 'build trg dictionary for train data'
os.system('cp ' + dict_path[0] + ' ' + dict_path[1])
else:
outname = os.path.join(train_dataset, self.train_dir_name)
for id in range(0, 2):
suffix = suffixes[id]
print 'build ' + suffix[1:] + ' dictionary for train data'
self.build_dict(outname + suffix, dict_path[id], dict_size)
print 'dictionary size is', self.dict_size
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