Datasets:
totto

	# coding=utf-8
	# Copyright 2020 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
	import json
	import os

	import datasets


	_DESCRIPTION = """\
	ToTTo is an open-domain English table-to-text dataset with over 120,000 training examples that proposes a controlled generation task: given a Wikipedia table and a set of highlighted table cells, produce a one-sentence description.
	"""
	_HOMEPAGE_URL = ""
	_URL = "https://storage.googleapis.com/totto-public/totto_data.zip"
	_CITATION = """\
	@inproceedings{parikh2020totto,
	title={{ToTTo}: A Controlled Table-To-Text Generation Dataset},
	author={Parikh, Ankur P and Wang, Xuezhi and Gehrmann, Sebastian and Faruqui, Manaal and Dhingra, Bhuwan and Yang, Diyi and Das, Dipanjan},
	booktitle={Proceedings of EMNLP},
	year={2020}
	}
	"""


	class Totto(datasets.GeneratorBasedBuilder):
	VERSION = datasets.Version("1.0.0")

	def _info(self):
	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=datasets.Features(
	{
	"id": datasets.Value("int32"),
	"table_page_title": datasets.Value("string"),
	"table_webpage_url": datasets.Value("string"),
	"table_section_title": datasets.Value("string"),
	"table_section_text": datasets.Value("string"),
	"table": [
	[
	{
	"column_span": datasets.Value("int32"),
	"is_header": datasets.Value("bool"),
	"row_span": datasets.Value("int32"),
	"value": datasets.Value("string"),
	}
	]
	],
	"highlighted_cells": datasets.Sequence(datasets.Sequence(datasets.Value("int32"))),
	"example_id": datasets.Value("string"),
	"sentence_annotations": datasets.Sequence(
	{
	"original_sentence": datasets.Value("string"),
	"sentence_after_deletion": datasets.Value("string"),
	"sentence_after_ambiguity": datasets.Value("string"),
	"final_sentence": datasets.Value("string"),
	}
	),
	"overlap_subset": datasets.Value("string"),
	},
	),
	supervised_keys=None,
	homepage=_HOMEPAGE_URL,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	path = dl_manager.download_and_extract(_URL)
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"datapath": os.path.join(path, "totto_data/totto_train_data.jsonl"),
	"datatype": "train",
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	gen_kwargs={
	"datapath": os.path.join(path, "totto_data/totto_dev_data.jsonl"),
	"datatype": "valid",
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={
	"datapath": os.path.join(path, "totto_data/unlabeled_totto_test_data.jsonl"),
	"datatype": "test",
	},
	),
	]

	def _generate_examples(self, datapath, datatype):
	with open(datapath, "r", encoding="utf-8") as json_file:
	json_list = list(json_file)

	for example_counter, json_str in enumerate(json_list):
	result = json.loads(json_str)
	response = {
	"id": example_counter,
	"table_page_title": result["table_page_title"],
	"table_webpage_url": result["table_webpage_url"],
	"table_section_title": result["table_section_title"],
	"table_section_text": result["table_section_text"],
	"table": result["table"],
	"highlighted_cells": result["highlighted_cells"],
	"example_id": str(result["example_id"]),
	}
	if datatype == "train":
	response["overlap_subset"] = "none"
	else:
	response["overlap_subset"] = str(result["overlap_subset"])

	if datatype == "test":
	response["sentence_annotations"] = [
	{
	"original_sentence": "none",
	"sentence_after_deletion": "none",
	"sentence_after_ambiguity": "none",
	"final_sentence": "none",
	}
	]
	else:
	response["sentence_annotations"] = result["sentence_annotations"]
	yield example_counter, response