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numerical_reasoning_arithmetic

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numerical_reasoning_arithmetic / numerical_reasoning_arithmetic.py

lintang

first operands are the subsets

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	# 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.
	# TODO: Address all TODOs and remove all explanatory comments
	"""TODO: Add a description here."""

	import datasets


	# TODO: Add BibTeX citation
	# Find for instance the citation on arxiv or on the dataset repo/website
	_CITATION = """\

	"""

	# TODO: Add description of the dataset here
	# You can copy an official description
	_DESCRIPTION = """\
	Generated dataset for testing numerical reasoning
	"""

	# 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 = ""

	class NumericalReasoningArithmetic(datasets.GeneratorBasedBuilder):
	"""TODO: Short description of my dataset."""

	VERSION = datasets.Version("0.1.0")

	BUILDER_CONFIGS = [
	datasets.BuilderConfig(
	name="{}".format(num),
	version=datasets.Version("0.1.0"),
	description="Task with {} as the first operand".format(num)) \
	for num in range(0,100)
	]

	DEFAULT_CONFIG_NAME = "multiplication"

	def _info(self):
	features = datasets.Features(
	{
	"x1": datasets.Value("int32"),
	"x2": datasets.Value("int32"),
	"y_mul": datasets.Value("int32"),
	"y_add": datasets.Value("int32"),
	}
	)

	return datasets.DatasetInfo(
	description=_DESCRIPTION,
	features=features,
	homepage=_HOMEPAGE,
	license=_LICENSE,
	citation=_CITATION,
	)

	def _split_generators(self, dl_manager):
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={
	"split": "test"
	},
	),
	]

	def _generate_examples(self, split):

	x1 = int(self.config.name)
	for key, x2 in enumerate(range(1,51)):
	yield key, {
	"x1": x1,
	"x2": x2,
	"y_mul": x1*x2,
	"y_add": x1+x2,
	}