| """Lynx""" | |
| import datasets | |
| import pandas as pd | |
| from collections import deque | |
| _CITATION = """ | |
| @inproceedings{li2018helpful, | |
| title={Helpful or Not? An investigation on the feasibility of identifier splitting via CNN-BiLSTM-CRF.}, | |
| author={Li, Jiechu and Du, Qingfeng and Shi, Kun and He, Yu and Wang, Xin and Xu, Jincheng}, | |
| booktitle={SEKE}, | |
| pages={175--174}, | |
| year={2018} | |
| } | |
| """ | |
| _DESCRIPTION = """ | |
| In programming languages, identifiers are tokens (also called symbols) which name language entities. | |
| Some of the kinds of entities an identifier might denote include variables, types, labels, subroutines, and packages. | |
| Lynx is a dataset for identifier segmentation, | |
| i.e. the task of adding spaces between the words on a identifier. | |
| """ | |
| _URL = "https://raw.githubusercontent.com/ruanchaves/hashformers/master/datasets/lynx.txt" | |
| class Lynx(datasets.GeneratorBasedBuilder): | |
| VERSION = datasets.Version("1.0.0") | |
| def _info(self): | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=datasets.Features( | |
| { | |
| "index": datasets.Value("int32"), | |
| "identifier": datasets.Value("string"), | |
| "segmentation": datasets.Value("string"), | |
| "expansion": datasets.Value("string") | |
| } | |
| ), | |
| supervised_keys=None, | |
| homepage="", | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager): | |
| downloaded_files = dl_manager.download(_URL) | |
| return [ | |
| datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files}), | |
| ] | |
| def _generate_examples(self, filepath): | |
| def get_segmentation(needle, haystack): | |
| output = "" | |
| haystack = iter(haystack) | |
| for char in needle: | |
| while True: | |
| try: | |
| next_char = next(haystack) | |
| if next_char == char: | |
| output += next_char | |
| break | |
| elif next_char.isspace(): | |
| output += next_char | |
| except StopIteration: | |
| break | |
| return output | |
| with open(filepath, "r") as f: | |
| for idx, line in enumerate(f): | |
| fields = line.split(":") | |
| identifier = fields[0].strip() | |
| expansion = fields[1].strip() | |
| yield idx, { | |
| "index": idx, | |
| "identifier": identifier, | |
| "segmentation": get_segmentation(identifier, expansion), | |
| "expansion": expansion | |
| } |