Datasets:

PhilipMay
/

stsb_multi_mt

	# coding=utf-8
	# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
	#
	# 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.
	"""These are different multilingual translations and the English original of the STSbenchmark dataset."""


	import csv

	import datasets


	_CITATION = """\
	@InProceedings{huggingface:dataset:stsb_multi_mt,
	title = {Machine translated multilingual STS benchmark dataset.},
	author={Philip May},
	year={2021},
	url={https://github.com/PhilipMay/stsb-multi-mt}
	}
	"""

	_DESCRIPTION = """\
	These are different multilingual translations and the English original of the STSbenchmark dataset. \
	Translation has been done with deepl.com.
	"""

	_HOMEPAGE = "https://github.com/PhilipMay/stsb-multi-mt"

	_LICENSE = "custom license - see project page"

	_BASE_URL = "https://raw.githubusercontent.com/PhilipMay/stsb-multi-mt/main/data"


	class StsbMultiMt(datasets.GeneratorBasedBuilder):
	"""These are different multilingual translations and the English original of the STSbenchmark dataset.

	Translation has been done with deepl.com.
	"""

	VERSION = datasets.Version("1.0.0")

	BUILDER_CONFIGS = [
	datasets.BuilderConfig(
	name="en",
	version=VERSION,
	description="This is the original English STS benchmark data set.",
	),
	datasets.BuilderConfig(
	name="de",
	version=VERSION,
	description="This is the German STS benchmark data set.",
	),
	datasets.BuilderConfig(
	name="es",
	version=VERSION,
	description="This is the Spanish STS benchmark data set.",
	),
	datasets.BuilderConfig(
	name="fr",
	version=VERSION,
	description="This is the French STS benchmark data set.",
	),
	datasets.BuilderConfig(
	name="it",
	version=VERSION,
	description="This is the Italian STS benchmark data set.",
	),
	# here seems to be an issue - see https://github.com/PhilipMay/stsb-multi-mt/issues/1
	# datasets.BuilderConfig(name="ja", version=VERSION, description="This is the Japanese STS benchmark data set."),
	datasets.BuilderConfig(
	name="nl",
	version=VERSION,
	description="This is the Dutch STS benchmark data set.",
	),
	datasets.BuilderConfig(
	name="pl",
	version=VERSION,
	description="This is the Polish STS benchmark data set.",
	),
	datasets.BuilderConfig(
	name="pt",
	version=VERSION,
	description="This is the Portuguese STS benchmark data set.",
	),
	datasets.BuilderConfig(
	name="ru",
	version=VERSION,
	description="This is the Russian STS benchmark data set.",
	),
	datasets.BuilderConfig(
	name="zh",
	version=VERSION,
	description="This is the Chinese (simplified) STS benchmark data set.",
	),
	]

	def _info(self):
	features = datasets.Features(
	{
	"sentence1": datasets.Value("string"),
	"sentence2": datasets.Value("string"),
	"similarity_score": datasets.Value("float"),
	}
	)
	return datasets.DatasetInfo(
	# This is the description that will appear on the datasets page.
	description=_DESCRIPTION,
	# This defines the different columns of the dataset and their types
	features=features, # Here we define them above because they are different between the two configurations
	# If there's a common (input, target) tuple from the features,
	# specify them here. They'll be used if as_supervised=True in
	# builder.as_dataset.
	supervised_keys=None,
	# Homepage of the dataset for documentation
	homepage=_HOMEPAGE,
	# License for the dataset if available
	license=_LICENSE,
	# Citation for the dataset
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	"""Returns SplitGenerators."""
	urls_to_download = {
	"train": f"{_BASE_URL}/stsb-{self.config.name}-train.csv",
	"dev": f"{_BASE_URL}/stsb-{self.config.name}-dev.csv",
	"test": f"{_BASE_URL}/stsb-{self.config.name}-test.csv",
	}
	downloaded_files = dl_manager.download(urls_to_download)
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	# These kwargs will be passed to _generate_examples
	gen_kwargs={
	"filepath": downloaded_files["train"],
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	# These kwargs will be passed to _generate_examples
	gen_kwargs={
	"filepath": downloaded_files["test"],
	},
	),
	datasets.SplitGenerator(
	name=datasets.NamedSplit("dev"),
	# These kwargs will be passed to _generate_examples
	gen_kwargs={
	"filepath": downloaded_files["dev"],
	},
	),
	]

	def _generate_examples(
	self,
	filepath, # 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, newline="", encoding="utf-8") as csvfile:
	csv_dict_reader = csv.DictReader(
	csvfile,
	fieldnames=["sentence1", "sentence2", "similarity_score"],
	dialect="excel",
	)
	for id_, row in enumerate(csv_dict_reader):
	# do asserts
	assert "sentence1" in row
	assert isinstance(row["sentence1"], str)
	assert len(row["sentence1"].strip()) > 0
	assert "sentence2" in row
	assert isinstance(row["sentence2"], str)
	assert len(row["sentence2"].strip()) > 0
	assert "similarity_score" in row
	assert isinstance(row["similarity_score"], str)
	assert len(row["similarity_score"].strip()) > 0

	# convert similarity_score from str to float
	row["similarity_score"] = float(row["similarity_score"])

	# do more asserts
	assert row["similarity_score"] >= 0.0
	assert row["similarity_score"] <= 5.0

	yield id_, row