# Copyright (c) 2020 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
import collections
from paddle.io import Dataset
from paddle.utils.download import get_path_from_url
from paddle.dataset.common import md5file
from paddlenlp.utils.env import DATA_HOME
from . import DatasetBuilder
__all__ = ['YahooAnswer100K']
[docs]class YahooAnswer100K(DatasetBuilder):
"""
The data is from https://arxiv.org/pdf/1702.08139.pdf, which samples 100k
documents from original Yahoo Answer data, and vocabulary size is 200k.
"""
URL = 'https://paddlenlp.bj.bcebos.com/datasets/yahoo-answer-100k.tar.gz'
MD5 = "68b88fd3f2cc9918a78047d99bcc6532"
META_INFO = collections.namedtuple('META_INFO', ('file', 'md5'))
SPLITS = {
'train': META_INFO(
os.path.join('yahoo-answer-100k', 'yahoo.train.txt'),
"3fb31bad56bae7c65fa084f702398c3b"),
'valid': META_INFO(
os.path.join('yahoo-answer-100k', 'yahoo.valid.txt'),
"2680dd89b4fe882359846b5accfb7647"),
'test': META_INFO(
os.path.join('yahoo-answer-100k', 'yahoo.test.txt'),
"3e6dcb643282e3543303980f1e21bb9d")
}
VOCAB_INFO = (os.path.join("yahoo-answer-100k", "vocab.txt"),
"2c17c7120e6240d34d19490404b5133d")
UNK_TOKEN = '_UNK'
def _get_data(self, mode, **kwargs):
default_root = os.path.join(DATA_HOME, self.__class__.__name__)
filename, data_hash = self.SPLITS[mode]
fullname = os.path.join(default_root, filename)
vocab_filename, vocab_hash = self.VOCAB_INFO
vocab_fullname = os.path.join(default_root, vocab_filename)
if (not os.path.exists(fullname)) or (
data_hash and not md5file(fullname) == data_hash) or (
not os.path.exists(vocab_fullname) or
(vocab_hash and not md5file(vocab_fullname) == vocab_hash)):
get_path_from_url(self.URL, default_root, self.MD5)
return fullname
def _read(self, filename, *args):
with open(filename, 'r', encoding='utf-8') as f:
for line in f:
line_stripped = line.strip()
yield {"sentence": line_stripped}
[docs] def get_vocab(self):
vocab_fullname = os.path.join(DATA_HOME, self.__class__.__name__,
self.VOCAB_INFO[0])
# Construct vocab_info to match the form of the input of `Vocab.load_vocabulary()` function
vocab_info = {'filepath': vocab_fullname, 'unk_token': self.UNK_TOKEN}
return vocab_info