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wisdomify
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story

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story / story.py

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9b5b745 over 2 years ago

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	import csv
	import os

	import datasets

	_CITATION = """\
	@Dataset{wisdomify:storyteller,
	title = {Korean proverb definitions and examples},
	author={Jongyoon Kim, Yubin Kim, Yongtaek Im
	},
	year={2021}
	}
	"""

	_DESCRIPTION = """\
	This dataset is designed to provide forward and reverse dictionary of Korean proverbs.
	"""

	# TODO: Add a link to an official homepage for the dataset here
	_HOMEPAGE = ""

	# TODO: Add the licence for the dataset here if you can find it
	_LICENSE = ""

	# TODO: Add link to the official dataset URLs here
	# If it is dropbox link, you must set 1 for query parameter "dl".
	_URLs = {
	'definition': "https://www.dropbox.com/s/4uh564afaimtob3/definition.zip?dl=1",
	'example': "https://www.dropbox.com/s/adlt9n6x5gjs0a6/example.zip?dl=1",
	}


	class Story(datasets.GeneratorBasedBuilder):
	# version must be "x.y.z' form
	VERSION = datasets.Version("0.0.0")

	BUILDER_CONFIGS = [
	datasets.BuilderConfig(name="definition", version=VERSION, description="definition"),
	datasets.BuilderConfig(name="example", version=VERSION, description="example"),
	]

	# This config is applied when user load dataset without "name".
	DEFAULT_CONFIG_NAME = "definition"

	def _info(self):
	# This method specifies the datasets.DatasetInfo object which contains information
	# and typings for the dataset

	if self.config.name == "definition":
	# These are the features of your dataset like images, labels ...
	features = datasets.Features(
	{
	"wisdom": datasets.Value("string"),
	"def": datasets.Value("string"),

	}
	)
	elif self.config.name == "example":
	features = datasets.Features(
	{
	"wisdom": datasets.Value("string"),
	"eg": datasets.Value("string"),
	}
	)
	else:
	raise NotImplementedError(f"Wrong name: {self.config.name}")

	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=features,
	supervised_keys=None,
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	# This method is used when user loads dataset.
	# dl_manager can be used to download and extract the dataset
	# and also can set split depending onf the configuration

	# Downloading data with _URLs
	downloaded_files = dl_manager.download_and_extract(_URLs[self.config.name])

	dtp = 'def' if self.config.name == "definition" else 'eg'

	train_path = os.path.join(downloaded_files, f'train_wisdom2{dtp}.tsv')
	val_path = os.path.join(downloaded_files, f'val_wisdom2{dtp}.tsv')
	test_path = os.path.join(downloaded_files, f'test_wisdom2{dtp}.tsv')

	return [
	# These gen_kwargs will be passed to _generate_examples
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={"filepath": train_path, "split": "train"},
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	gen_kwargs={"filepath": val_path, "split": "validation"},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={"filepath": test_path, "split": "test"},
	),
	]

	def _generate_examples(self, filepath, split):
	# method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
	""" Yields examples as (key, example) tuples. """
	# This method handles input defined in _split_generators to yield (key, example) tuples from the dataset.
	# The `key` is here for legacy reason (tfds) and is not important in itself.

	with open(filepath, encoding="utf-8") as f:
	tsv_reader = csv.reader(f, delimiter="\t")
	for id_, row in enumerate(tsv_reader):
	if id_ == 0:
	continue # first row shows column info

	if self.config.name == "definition":
	yield id_, {
	"wisdom": row[0],
	"def": row[1],
	}
	elif self.config.name == "example":
	yield id_, {
	"wisdom": row[0],
	"eg": row[1],
	}
	else:
	raise NotImplementedError(f"Wrong name: {self.config.name}")