Datasets:

thepurpleowl
/

codequeries

	# coding=utf-8
	# Copyright 2022 CodeQueries Authors and the 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.

	"""The CodeQueries benchmark."""


	import json
	import os

	import datasets

	logger = datasets.logging.get_logger(__name__)


	_CODEQUERIES_CITATION = """\
	@article{codequeries2022,
	title={Learning to Answer Semantic Queries over Code},
	author={A, B, C, D, E, F},
	journal={arXiv preprint arXiv:<.>},
	year={2022}
	}
	"""

	_IDEAL_DESCRIPTION = """\
	CodeQueries Ideal setup.

	"""

	_PREFIX_DESCRIPTION = """\
	CodeQueries Prefix setup."""

	_SLIDING_WINDOW_DESCRIPTION = """\
	CodeQueries Sliding window setup."""

	_FILE_IDEAL_DESCRIPTION = """\
	CodeQueries File level Ideal setup."""

	_TWOSTEP_DESCRIPTION = """\
	CodeQueries Twostep setup."""


	class CodequeriesConfig(datasets.BuilderConfig):
	"""BuilderConfig for Codequeries."""

	def __init__(self, features, citation, url, **kwargs):
	"""BuilderConfig for Codequeries.

	Args:
	features: `list[string]`, list of the features that will appear in the
	feature dict. Should not include "label".
	citation: `string`, citation for the data set.
	**kwargs: keyword arguments forwarded to super.
	"""
	# Version history:
	# 1.0.0: Initial version.
	super(CodequeriesConfig, self).__init__(version=datasets.Version("1.0.0"), **kwargs)
	self.features = features
	self.citation = citation
	self.url = url


	class Codequeries(datasets.GeneratorBasedBuilder):
	"""The Codequeries benchmark."""

	BUILDER_CONFIGS = [
	CodequeriesConfig(
	name="ideal",
	description=_IDEAL_DESCRIPTION,
	features=["query_name", "context_blocks", "answer_spans",
	"supporting_fact_spans", "code_file_path", "example_type",
	"subtokenized_input_sequence", "label_sequence"],
	citation=_CODEQUERIES_CITATION,
	# homepage="",
	# data_url="",
	url="",
	),
	# CodequeriesConfig(
	# name="prefix",
	# description=_PREFIX_DESCRIPTION,
	# features=["query_name", "context_blocks", "answer_spans",
	# "supporting_fact_spans", "code_file_path", "example_type",
	# "subtokenized_input_sequence", "label_sequence"],
	# citation=_CODEQUERIES_CITATION,
	# url="",
	# ),
	# CodequeriesConfig(
	# name="sliding_window",
	# description=_SLIDING_WINDOW_DESCRIPTION,
	# features=["query_name", "context_blocks", "answer_spans",
	# "supporting_fact_spans", "code_file_path", "example_type",
	# "subtokenized_input_sequence", "label_sequence"],
	# citation=_CODEQUERIES_CITATION,
	# url="",
	# ),
	CodequeriesConfig(
	name="file_ideal",
	description=_FILE_IDEAL_DESCRIPTION,
	features=["query_name", "context_blocks", "answer_spans",
	"supporting_fact_spans", "code_file_path", "example_type",
	"subtokenized_input_sequence", "label_sequence"],
	citation=_CODEQUERIES_CITATION,
	url="",
	),
	# CodequeriesConfig(
	# name="twostep",
	# description=_TWOSTEP_DESCRIPTION,
	# features=["query_name", "context_blocks", "answer_spans",
	# "supporting_fact_spans", "code_file_path", "example_type",
	# "subtokenized_input_sequence", "label_sequence"],
	# citation=_CODEQUERIES_CITATION,
	# url="",
	# ),
	]

	# DEFAULT_CONFIG_NAME = "ideal"

	def _info(self):
	# features = {feature: datasets.Value("string") for feature in self.config.features}
	features = {}
	features["query_name"] = datasets.Value("string")
	features["context_blocks"] = [
	{
	"content": datasets.Value("string"),
	"metadata": datasets.Value("string"),
	"header": datasets.Value("string")
	}
	]
	features["answer_spans"] = [
	{
	'span': datasets.Value("string"),
	'start_line': datasets.Value("int32"),
	'start_column': datasets.Value("int32"),
	'end_line': datasets.Value("int32"),
	'end_column': datasets.Value("int32")
	}
	]
	features["supporting_fact_spans"] = [
	{
	'span': datasets.Value("string"),
	'start_line': datasets.Value("int32"),
	'start_column': datasets.Value("int32"),
	'end_line': datasets.Value("int32"),
	'end_column': datasets.Value("int32")
	}
	]
	features["code_file_path"] = datasets.Value("string")
	features["example_type"] = datasets.Value("int32")
	features["subtokenized_input_sequence"] = datasets.features.Sequence(datasets.Value("string"))
	features["label_sequence"] = datasets.features.Sequence(datasets.Value("int32"))

	return datasets.DatasetInfo(
	description=self.config.description,
	features=datasets.Features(features),
	homepage=self.config.url,
	citation=_CODEQUERIES_CITATION,
	)

	def _split_generators(self, dl_manager):
	dl_dir = ""
	if self.config.name in ["prefix", "sliding_window", "file_ideal", "twostep"]:
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={
	"filepath": os.path.join(dl_dir, self.config.name + "_test.json"),
	"split": datasets.Split.TEST,
	},
	),
	]
	else:
	return [
	datasets.SplitGenerator(
	name=datasets.Split.TRAIN,
	gen_kwargs={
	"filepath": os.path.join(dl_dir, self.config.name + "_train.json"),
	"split": datasets.Split.TRAIN,
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.VALIDATION,
	gen_kwargs={
	"filepath": os.path.join(dl_dir, self.config.name + "_val.json"),
	"split": datasets.Split.VALIDATION,
	},
	),
	datasets.SplitGenerator(
	name=datasets.Split.TEST,
	gen_kwargs={
	"filepath": os.path.join(dl_dir, self.config.name + "_test.json"),
	"split": datasets.Split.TEST,
	},
	),
	]

	def _generate_examples(self, filepath, split):
	if self.config.name in ["prefix", "sliding_window", "file_ideal", "twostep"]:
	assert split == datasets.Split.TEST
	logger.info("generating examples from = %s", filepath)

	with open(filepath, encoding="utf-8") as f:
	key = 0
	for line in f:
	row = json.loads(line)

	instance_key = str(key) + "_" + row["query_name"] + "_" + row["code_file_path"]
	yield instance_key, {
	"query_name": row["query_name"],
	"context_blocks": row["context_blocks"],
	"answer_spans": row["answer_spans"],
	"supporting_fact_spans": row["supporting_fact_spans"],
	"code_file_path": row["code_file_path"],
	"example_type": row["example_type"],
	"subtokenized_input_sequence": row["subtokenized_input_sequence"],
	"label_sequence": row["label_sequence"],
	}
	key += 1