Add narrative qa
{'login': 'Varal7', 'id': 8019486, 'node_id': 'MDQ6VXNlcjgwMTk0ODY=', 'avatar_url': 'https://avatars.githubusercontent.com/u/8019486?v=4', 'gravatar_id': '', 'url': 'https://api.github.com/users/Varal7', 'html_url': 'https://github.com/Varal7', 'followers_url': 'https://api.github.com/users/Varal7/followers', 'following_url': 'https://api.github.com/users/Varal7/following{/other_user}', 'gists_url': 'https://api.github.com/users/Varal7/gists{/gist_id}', 'starred_url': 'https://api.github.com/users/Varal7/starred{/owner}{/repo}', 'subscriptions_url': 'https://api.github.com/users/Varal7/subscriptions', 'organizations_url': 'https://api.github.com/users/Varal7/orgs', 'repos_url': 'https://api.github.com/users/Varal7/repos', 'events_url': 'https://api.github.com/users/Varal7/events{/privacy}', 'received_events_url': 'https://api.github.com/users/Varal7/received_events', 'type': 'User', 'site_admin': False}
[]
[]
['Does it make sense to download the full stories? I remember attempting to implement this dataset a while ago and ended up with something like:\r\n```python\r\n    def _split_generators(self, dl_manager):\r\n        """Returns SplitGenerators."""\r\n\r\n        dl_dir = dl_manager.download_and_extract(_DOWNLOAD_URL)\r\n        data_dir = os.path.join(dl_dir, "narrativeqa-master")\r\n\r\n        urls = {"test":{}, "train": {},"valid":{}}\r\n        with open(os.path.join(data_dir,"documents.csv")) as f_in:\r\n            csv_reader = csv.reader(f_in)\r\n            next(csv_reader) # discard header row\r\n            for i,row in enumerate(csv_reader):\r\n                if i > 1572:\r\n                    break\r\n                if row != []:\r\n                    urls[row[1]][row[0]] = row[3]\r\n\r\n        url_files = {}\r\n        for key in urls.keys():\r\n            url_files[key] = dl_manager.download_and_extract(urls[key])\r\n\r\n        return [\r\n            nlp.SplitGenerator(\r\n                name=nlp.Split.TRAIN,\r\n                gen_kwargs={\r\n                    "data_dir":data_dir,\r\n                    "split":"train",\r\n                    "doc_id_to_path":url_files["train"]\r\n                    }\r\n            ),\r\n        ....\r\n```\r\nIt does end up cluttering your huggingface cache dir though.'
 'Also since there doesn\'t seem to be any meaning in the order of answer_1 and answer_2, it might make sense to combine them (see [squad.py](https://github.com/huggingface/nlp/blob/8b0ffc85e4e52ae1f18d31be99b6c70b82c991ca/datasets/squad/squad.py#L86-L88)):\r\n```python\r\n"answers": nlp.features.Sequence({\r\n    "text": nlp.Value("string"),\r\n    "tokenized": nlp.features.Sequence(nlp.Value("string"))\r\n})\r\n```\r\n(the tokenized features should also probably be lists of strings not just strings - see [natural_questions.py](https://github.com/huggingface/nlp/blob/4cd34287300a1135ce7b22f6dd209ca305c71b3a/datasets/natural_questions/natural_questions.py#L83))\r\n\r\nAgain, this is a personal preference thing, but it might be useful to combine the document-related features:\r\n```python\r\n{\r\n    "document": {\r\n        "id": nlp.Value("string"),\r\n        "kind": nlp.Value("string"),\r\n        "url": nlp.Value("string"),\r\n        "file_size": nlp.Value("int32"),\r\n        "word_count": nlp.Value("int32"),\r\n        "start": nlp.Value("string"),\r\n        "end": nlp.Value("string"),\r\n        "wiki_url": nlp.Value("string"),\r\n        "wiki_title": nlp.Value("string"),\r\n        "summary": nlp.features.Sequence({\r\n            "text": nlp.Value("string"),\r\n            "tokens": nlp.features.Sequence(nlp.Value("string"))\r\n        }),\r\n        "text": nlp.Value("string"),\r\n    },\r\n    "question": nlp.features.Sequence({\r\n        "text": nlp.Value("string"),\r\n        "tokens": nlp.features.Sequence(nlp.Value("string"))\r\n    }),\r\n    "answers": nlp.features.Sequence({\r\n        "text": nlp.Value("string"),\r\n        "tokens": nlp.features.Sequence(nlp.Value("string"))\r\n    })\r\n}\r\n```'
 'Did you manage to fix the dummy data @Varal7 ?'
 "@lhoestq do you think it's acceptable for the `dl_manager` to go grab all the individual stories from project gutenburg? I've got a working version of that but it does clutter up your huggingface cache somewhat.\r\n\r\nThe real value (and original purpose) of this dataset is doing question answering on the full text."
 "> @lhoestq do you think it's acceptable for the `dl_manager` to go grab all the individual stories from project gutenburg? I've got a working version of that but it does clutter up your huggingface cache somewhat.\r\n> \r\n> The real value (and original purpose) of this dataset is doing question answering on the full text.\r\n\r\nWhat's the problem exactly with the cache ?"
 "Nothing, just that because each story is a separate download it gets a bit messy as all 1573 files are under `~/.cache/hugginface/datasets` rather than organized under a subdir.\r\n\r\nProbably doesn't matter to the end user though."
 "Yea I agree it's a mess. I just created #393 to make things easier."
 "I got the PR merged to have a cleaner the cache directory (everything is downloaded inside the 'downloads' sub-directory).\r\nFeel free to download all the stories then @ghomasHudson @Varal7  x)\r\nIf you have the possibility of downloading a compressed file with most of the stories at once it would be better though."
 "Looks good @lhoestq . The problem I'm having at the moment is that stories from project Gutenberg occasionally fail. All books are out of copyright so we should be able to host them. \r\n\r\nHere's a zip file of the full text if we have anywhere to put them: https://drive.google.com/file/d/17jOR7NqvzDwSlPXrlHaYV-PGI8JG-KY5/view?usp=sharing\r\n"
 'I put the zip file here @ghomasHudson \r\nhttps://storage.googleapis.com/huggingface-nlp/datasets/narrative_qa/narrativeqa_full_text.zip\r\n\r\nSorry for the delay'
 'Closing in favor of #499']
{'url': 'https://api.github.com/repos/huggingface/datasets/pulls/309', 'html_url': 'https://github.com/huggingface/datasets/pull/309', 'diff_url': 'https://github.com/huggingface/datasets/pull/309.diff', 'patch_url': 'https://github.com/huggingface/datasets/pull/309.patch', 'merged_at': None}
Test cases for dummy data don't pass

Only contains data for summaries (not whole story)
{'url': 'https://api.github.com/repos/huggingface/datasets/issues/309/reactions', 'total_count': 0, '+1': 0, '-1': 0, 'laugh': 0, 'hooray': 0, 'confused': 0, 'heart': 0, 'rocket': 0, 'eyes': 0}