Datasets:

google
/

code_x_glue_tc_text_to_code

	import json
	from typing import List

	import datasets

	from .common import Child
	from .generated_definitions import DEFINITIONS


	_DESCRIPTION = """We use concode dataset which is a widely used code generation dataset from Iyer's EMNLP 2018 paper Mapping Language to Code in Programmatic Context. See paper for details."""
	_CITATION = """@article{iyer2018mapping,
	title={Mapping language to code in programmatic context},
	author={Iyer, Srinivasan and Konstas, Ioannis and Cheung, Alvin and Zettlemoyer, Luke},
	journal={arXiv preprint arXiv:1808.09588},
	year={2018}
	}"""


	class CodeXGlueTcTextToCodeImpl(Child):
	_DESCRIPTION = _DESCRIPTION
	_CITATION = _CITATION

	_FEATURES = {
	"id": datasets.Value("int32"), # Index of the sample
	"nl": datasets.Value("string"), # The natural language description of the task
	"code": datasets.Value("string"), # The programming source code for the task
	}

	_SUPERVISED_KEYS = ["code"]

	SPLITS = {"train": datasets.Split.TRAIN, "dev": datasets.Split.VALIDATION, "test": datasets.Split.TEST}

	def generate_urls(self, split_name):
	yield "data", f"concode/{split_name}.json"

	def _generate_examples(self, split_name, file_paths):
	with open(file_paths["data"], encoding="utf-8") as f:
	for idx, line in enumerate(f):
	entry = json.loads(line)
	entry["id"] = idx
	yield idx, entry


	CLASS_MAPPING = {
	"CodeXGlueTcTextToCode": CodeXGlueTcTextToCodeImpl,
	}


	class CodeXGlueTcTextToCode(datasets.GeneratorBasedBuilder):
	BUILDER_CONFIG_CLASS = datasets.BuilderConfig
	BUILDER_CONFIGS = [
	datasets.BuilderConfig(name=name, description=info["description"]) for name, info in DEFINITIONS.items()
	]

	def _info(self):
	name = self.config.name
	info = DEFINITIONS[name]
	if info["class_name"] in CLASS_MAPPING:
	self.child = CLASS_MAPPING[info["class_name"]](info)
	else:
	raise RuntimeError(f"Unknown python class for dataset configuration {name}")
	ret = self.child._info()
	return ret

	def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
	return self.child._split_generators(dl_manager=dl_manager)

	def _generate_examples(self, split_name, file_paths):
	return self.child._generate_examples(split_name, file_paths)