wmt14.py 3.6 KB
Newer Older
H
Helin Wang 已提交
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16
# 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
"""
Q
qiaolongfei 已提交
17 18 19
import tarfile

import paddle.v2.dataset.common
H
Helin Wang 已提交
20 21 22 23 24

__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'
25
# this is a small set of data for test. The original data is too large and will be add later.
Q
qiaolongfei 已提交
26
URL_TRAIN = 'http://paddlepaddle.bj.bcebos.com/demo/wmt_shrinked_data/wmt14.tgz'
Q
qiaolongfei 已提交
27
MD5_TRAIN = 'a755315dd01c2c35bde29a744ede23a6'
Q
qiaolongfei 已提交
28 29 30 31 32 33

START = "<s>"
END = "<e>"
UNK = "<unk>"
UNK_IDX = 2

Q
qiaolongfei 已提交
34 35 36

def __read_to_dict__(tar_file, dict_size):
    def __to_dict__(fd, size):
Q
qiaolongfei 已提交
37
        out_dict = dict()
Q
qiaolongfei 已提交
38 39
        for line_count, line in enumerate(fd):
            if line_count < size:
Q
qiaolongfei 已提交
40 41 42
                out_dict[line.strip()] = line_count
            else:
                break
Q
qiaolongfei 已提交
43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67
        return out_dict

    with tarfile.open(tar_file, mode='r') as f:
        names = [
            each_item.name for each_item in f
            if each_item.name.endswith("src.dict")
        ]
        assert len(names) == 1
        src_dict = __to_dict__(f.extractfile(names[0]), dict_size)
        names = [
            each_item.name for each_item in f
            if each_item.name.endswith("trg.dict")
        ]
        assert len(names) == 1
        trg_dict = __to_dict__(f.extractfile(names[0]), dict_size)
        return src_dict, trg_dict


def reader_creator(tar_file, file_name, dict_size):
    def reader():
        src_dict, trg_dict = __read_to_dict__(tar_file, dict_size)
        with tarfile.open(tar_file, mode='r') as f:
            names = [
                each_item.name for each_item in f
                if each_item.name.endswith(file_name)
H
Helin Wang 已提交
68
            ]
Q
qiaolongfei 已提交
69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105
            for name in names:
                for line in f.extractfile(name):
                    line_split = line.strip().split('\t')
                    if len(line_split) != 2:
                        continue
                    src_seq = line_split[0]  # one source sequence
                    src_words = src_seq.split()
                    src_ids = [
                        src_dict.get(w, UNK_IDX)
                        for w in [START] + src_words + [END]
                    ]

                    trg_seq = line_split[1]  # one target sequence
                    trg_words = trg_seq.split()
                    trg_ids = [trg_dict.get(w, UNK_IDX) for w in trg_words]

                    # remove sequence whose length > 80 in training mode
                    if len(src_ids) > 80 or len(trg_ids) > 80:
                        continue
                    trg_ids_next = trg_ids + [trg_dict[END]]
                    trg_ids = [trg_dict[START]] + trg_ids

                    yield src_ids, trg_ids, trg_ids_next

    return reader


def train(dict_size):
    return reader_creator(
        paddle.v2.dataset.common.download(URL_TRAIN, 'wmt14', MD5_TRAIN),
        'train/train', dict_size)


def test(dict_size):
    return reader_creator(
        paddle.v2.dataset.common.download(URL_TRAIN, 'wmt14', MD5_TRAIN),
        'test/test', dict_size)