Datasets:

Languages:
code
Multilinguality:
monolingual
Size Categories:
unknown
Language Creators:
machine-generated
Annotations Creators:
expert-generated
Source Datasets:
original
License:
lynx / lynx.py
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"""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
}