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# coding=utf-8
# Copyright 2020 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
#
# 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.

# Lint as: python3
"""SituatedQA: Incorporating Extra-Linguistic Contexts into QA."""


import json
import re
import datasets


logger = datasets.logging.get_logger(__name__)


_CITATION = """\
@article{ zhang2021situatedqa,
  title={ {S}ituated{QA}: Incorporating Extra-Linguistic Contexts into {QA} },
  author={ Zhang, Michael J.Q. and Choi, Eunsol },
  journal={ Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP) },
  year={ 2021 }
}
"""

_DESCRIPTION = """\
"""

_URL = "https://raw.githubusercontent.com/mikejqzhang/SituatedQA/master/data/qa_data/"
_URLS = {
    "geo_train": _URL + "geo.train.jsonl",
    "geo_dev": _URL + "geo.dev.jsonl",
    "geo_test": _URL + "geo.test.jsonl",
    "temp_train": _URL + "temp.train.jsonl",
    "temp_dev": _URL + "temp.dev.jsonl",
    "temp_test": _URL + "temp.test.jsonl",
}

class SituatedQAConfig(datasets.BuilderConfig):

    def __init__(self, **kwargs):
        """BuilderConfig
        Args:
          **kwargs: keyword arguments forwarded to super.
        """
        super(SituatedQAConfig, self).__init__(**kwargs)


class Squall(datasets.GeneratorBasedBuilder):

    BUILDER_CONFIGS = [
        SituatedQAConfig(name = 'geo'),
        SituatedQAConfig(name = 'temp')]
    
    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "question": datasets.Value("string"),
                    "id": datasets.Value("string"),
                    "edited_question": datasets.Value("string"),
                    "date": datasets.Value("string"),
                    "date_type": datasets.Value("string"),
                    "location": datasets.Value("string"),
                    "answer": datasets.features.Sequence(datasets.Value("string")),
                    "any_answer": datasets.features.Sequence(datasets.Value("string")),
                }
            ),
            # No default supervised_keys (as we have to pass both question
            # and context as input).
            supervised_keys=None,
            homepage="https://github.com/mikejqzhang/SituatedQA/tree/master",
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        urls_to_download = {
            "geo_train": _URLS["geo_train"],
            "geo_dev": _URLS["geo_dev"],
            "geo_test": _URLS["geo_test"],
            "temp_train": _URLS["temp_train"],
            "temp_dev": _URLS["temp_dev"],
            "temp_test": _URLS["temp_test"],
        }
        downloaded_files = dl_manager.download_and_extract(urls_to_download)

        if self.config.name == 'geo':
            train_file = downloaded_files["geo_train"]
            dev_file = downloaded_files["geo_dev"]
            test_file = downloaded_files["geo_test"]
        else:
            train_file = downloaded_files["temp_train"]
            dev_file = downloaded_files["temp_dev"]
            test_file = downloaded_files["temp_test"]

        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN, 
                gen_kwargs={"split_key": "train", "filepath": train_file}),
            datasets.SplitGenerator(
                name=datasets.Split.VALIDATION, 
                gen_kwargs={"split_key": "dev", "filepath": dev_file}),
            datasets.SplitGenerator(
                name=datasets.Split.TEST, 
                gen_kwargs={"split_key": "test", "filepath": test_file}),
        ]

    def _generate_examples(self, split_key, filepath):
        """This function returns the examples in the raw (text) form."""
        logger.info("generating examples from = %s", filepath)

        with open(filepath, 'r') as file:
            json_list = list(file)
 
        for i, line in enumerate(json_list):
            data = json.loads(line)
            if 'location' not in data:
                data['location']=''
            if 'date' not in data:
                data['date']=''
            if 'date_type' not in data:
                data['date_type']=''
                
            yield i, {
                "question": data["question"],
                "id": str(data["id"]),
                "edited_question": data["edited_question"],
                "date": data["date"],
                "date_type": data["date_type"],
                "location": data["location"],
                "answer": data["answer"],
                "any_answer": data["any_answer"]
            }