text: # 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 collections
  import json
  import os
  
  from paddle.dataset.common import md5file
  from paddle.utils.download import get_path_from_url
  from paddlenlp.utils.env import DATA_HOME
  from . import DatasetBuilder
  
  __all__ = ['SQuAD']
  
  
  class SQuAD(DatasetBuilder):
      '''
      Stanford Question Answering Dataset (SQuAD) is a reading comprehension 
      dataset, consisting of questions posed by crowdworkers on a set of Wikipedia
      articles, where the answer to every question is a segment of text, or span, 
      from the corresponding reading passage, or the question might be unanswerable.
      '''
      META_INFO = collections.namedtuple('META_INFO', ('file', 'md5', 'URL'))
      SPLITS = {
          'train_v1': META_INFO(
              os.path.join('train-v1.1.json'), '981b29407e0affa3b1b156f72073b945',
              'https://paddlenlp.bj.bcebos.com/datasets/squad/train-v1.1.json'),
          'dev_v1': META_INFO(
              os.path.join('dev-v1.1.json'), '3e85deb501d4e538b6bc56f786231552',
              'https://paddlenlp.bj.bcebos.com/datasets/squad/dev-v1.1.json'),
          'train_v2': META_INFO(
              os.path.join('train-v2.0.json'), '62108c273c268d70893182d5cf8df740',
              'https://paddlenlp.bj.bcebos.com/datasets/squad/train-v2.0.json'),
          'dev_v2': META_INFO(
              os.path.join('dev-v2.0.json'), '246adae8b7002f8679c027697b0b7cf8',
              'https://paddlenlp.bj.bcebos.com/datasets/squad/dev-v2.0.json')
      }
  
      def _get_data(self, mode, **kwargs):
          default_root = os.path.join(DATA_HOME, self.__class__.__name__)
          filename, data_hash, URL = self.SPLITS[mode]
          fullname = os.path.join(default_root, filename)
          if not os.path.exists(fullname) or (data_hash and
                                              not md5file(fullname) == data_hash):
              get_path_from_url(URL, default_root)
  
          return fullname
  
      def _read(self, filename, *args):
          with open(filename, "r", encoding="utf8") as f:
              input_data = json.load(f)["data"]
          for entry in input_data:
              title = entry.get("title", "").strip()
              for paragraph in entry["paragraphs"]:
                  context = paragraph["context"].strip()
                  for qa in paragraph["qas"]:
                      qas_id = qa["id"]
                      question = qa["question"].strip()
                      answer_starts = []
                      answers = []
                      is_impossible = False
  
                      if "is_impossible" in qa.keys():
                          is_impossible = qa["is_impossible"]
  
                      answer_starts = [
                          answer["answer_start"] for answer in qa["answers"]
                      ]
                      answers = [
                          answer["text"].strip() for answer in qa["answers"]
                      ]
  
                      yield {
                          'id': qas_id,
                          'title': title,
                          'context': context,
                          'question': question,
                          'answers': answers,
                          'answer_starts': answer_starts,
                          'is_impossible': is_impossible
                      }
  