提交 d6c6a996 编写于 作者: H Helin Wang

dataset reader for wmt14

example usage:

import paddle.v2 as paddle

if __name__ == '__main__':
    dict_en, dict_fr =	paddle.dataset.wmt14.build_dict()
    train = paddle.dataset.wmt14.train(dict_en, dict_fr)
    test = paddle.dataset.wmt14.test(dict_en, dict_fr)

    total_train = 0
    for i in train():
        total_train += 1

    total_test = 0
    for i in test():
        total_test += 1

    print total_train, total_test
上级 349e799e
...@@ -20,8 +20,9 @@ import movielens ...@@ -20,8 +20,9 @@ import movielens
import conll05 import conll05
import uci_housing import uci_housing
import sentiment import sentiment
import wmt14
__all__ = [ __all__ = [
'mnist', 'imikolov', 'imdb', 'cifar', 'movielens', 'conll05', 'sentiment' 'mnist', 'imikolov', 'imdb', 'cifar', 'movielens', 'conll05', 'sentiment'
'uci_housing' 'uci_housing', 'wmt14'
] ]
# 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.
"""
wmt14 dataset
"""
import paddle.v2.dataset.common
import tarfile
import os.path
import itertools
__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:8000/train.tgz'
MD5_TRAIN = '72de99da2830ea5a3a2c4eb36092bbc7'
def word_count(f, word_freq=None):
add = paddle.v2.dataset.common.dict_add
if word_freq == None:
word_freq = {}
for l in f:
for w in l.strip().split():
add(word_freq, w)
add(word_freq, '<s>')
add(word_freq, '<e>')
return word_freq
def get_word_dix(word_freq):
TYPO_FREQ = 50
word_freq = filter(lambda x: x[1] > TYPO_FREQ, word_freq.items())
word_freq_sorted = sorted(word_freq, key=lambda x: (-x[1], x[0]))
words, _ = list(zip(*word_freq_sorted))
word_idx = dict(zip(words, xrange(len(words))))
word_idx['<unk>'] = len(words)
return word_idx
def get_word_freq(train, dev):
word_freq = word_count(train, word_count(dev))
if '<unk>' in word_freq:
# remove <unk> for now, since we will set it as last index
del word_freq['<unk>']
return word_freq
def build_dict():
base_dir = './wmt14-data'
train_en_filename = base_dir + '/train/train.en'
train_fr_filename = base_dir + '/train/train.fr'
dev_en_filename = base_dir + '/dev/ntst1213.en'
dev_fr_filename = base_dir + '/dev/ntst1213.fr'
if not os.path.exists(train_en_filename) or not os.path.exists(
train_fr_filename):
with tarfile.open(
paddle.v2.dataset.common.download(URL_TRAIN, 'wmt14',
MD5_TRAIN)) as tf:
tf.extractall(base_dir)
if not os.path.exists(dev_en_filename) or not os.path.exists(
dev_fr_filename):
with tarfile.open(
paddle.v2.dataset.common.download(URL_DEV_TEST, 'wmt14',
MD5_DEV_TEST)) as tf:
tf.extractall(base_dir)
f_en = open(train_en_filename)
f_fr = open(train_fr_filename)
f_en_dev = open(dev_en_filename)
f_fr_dev = open(dev_fr_filename)
word_freq_en = get_word_freq(f_en, f_en_dev)
word_freq_fr = get_word_freq(f_fr, f_fr_dev)
f_en.close()
f_fr.close()
f_en_dev.close()
f_fr_dev.close()
return get_word_dix(word_freq_en), get_word_dix(word_freq_fr)
def reader_creator(directory, path_en, path_fr, URL, MD5, dict_en, dict_fr):
def reader():
if not os.path.exists(path_en) or not os.path.exists(path_fr):
with tarfile.open(
paddle.v2.dataset.common.download(URL, 'wmt14', MD5)) as tf:
tf.extractall(directory)
f_en = open(path_en)
f_fr = open(path_fr)
UNK_en = dict_en['<unk>']
UNK_fr = dict_fr['<unk>']
for en, fr in itertools.izip(f_en, f_fr):
src_ids = [dict_en.get(w, UNK_en) for w in en.strip().split()]
tar_ids = [
dict_fr.get(w, UNK_fr)
for w in ['<s>'] + fr.strip().split() + ['<e>']
]
# remove sequence whose length > 80 in training mode
if len(src_ids) == 0 or len(tar_ids) <= 1 or len(
src_ids) > 80 or len(tar_ids) > 80:
continue
yield src_ids, tar_ids[:-1], tar_ids[1:]
f_en.close()
f_fr.close()
return reader
def train(dict_en, dict_fr):
directory = './wmt14-data'
return reader_creator(directory, directory + '/train/train.en',
directory + '/train/train.fr', URL_TRAIN, MD5_TRAIN,
dict_en, dict_fr)
def test(dict_en, dict_fr):
directory = './wmt14-data'
return reader_creator(directory, directory + '/dev/ntst1213.en',
directory + '/dev/ntst1213.fr', URL_DEV_TEST,
MD5_DEV_TEST, dict_en, dict_fr)
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