Datasets:
Tasks:
Text Generation
Modalities:
Text
Sub-tasks:
language-modeling
Languages:
English
Size:
10M - 100M
License:
# -*- coding: utf-8 -*- | |
""" | |
@author:XuMing(xuming624@qq.com) | |
@description: | |
""" | |
"""Code AutoComplete Python dataset Corpus.(code_autocomplete)""" | |
import os | |
import datasets | |
_DESCRIPTION = """纯文本数据,内容:高质量编程源代码,包括Python,Java,CPP源代码""" | |
PYTHON_HOME = "https://github.com/bharathgs/Awesome-pytorch-list" | |
JAVA_HOME = "https://github.com/akullpp/awesome-java" | |
CPP_HOME = "https://github.com/fffaraz/awesome-cpp" | |
_CITATION = "https://github.com/shibing624/code-autocomplete" | |
_DATA_URL = "https://github.com/shibing624/code-autocomplete/releases/download/0.0.4/source_code.zip" | |
class SourceCodeConfig(datasets.BuilderConfig): | |
"""BuilderConfig for NLI_zh""" | |
def __init__(self, features, data_url, citation, url, **kwargs): | |
"""BuilderConfig for NLI_zh | |
Args: | |
features: `list[string]`, list of the features that will appear in the | |
feature dict. Should not include "label". | |
data_url: `string`, url to download the zip file from. | |
citation: `string`, citation for the data set. | |
url: `string`, url for information about the data set. | |
**kwargs: keyword arguments forwarded to super. | |
""" | |
super().__init__(version=datasets.Version("1.0.0"), **kwargs) | |
self.features = features | |
self.data_url = data_url | |
self.citation = citation | |
self.url = url | |
class SourceCode(datasets.GeneratorBasedBuilder): | |
"""The Natural Language Inference Chinese(NLI_zh) Corpus.""" | |
BUILDER_CONFIGS = [ | |
SourceCodeConfig( | |
name="python", | |
description=_DESCRIPTION, | |
features=["text"], | |
data_url=_DATA_URL, | |
citation=_CITATION, | |
url=PYTHON_HOME, | |
), | |
SourceCodeConfig( | |
name="java", | |
description=_DESCRIPTION, | |
features=["text"], | |
data_url=_DATA_URL, | |
citation=_CITATION, | |
url=JAVA_HOME, | |
), | |
SourceCodeConfig( | |
name="cpp", | |
description=_DESCRIPTION, | |
features=["text"], | |
data_url=_DATA_URL, | |
citation=_CITATION, | |
url=CPP_HOME, | |
), | |
] | |
def _info(self): | |
return datasets.DatasetInfo( | |
description=self.config.description, | |
features=datasets.Features( | |
{ | |
"text": datasets.Value("string"), | |
} | |
), | |
homepage=self.config.url, | |
citation=self.config.citation, | |
) | |
def _split_generators(self, dl_manager): | |
dl_dir = dl_manager.download_and_extract(self.config.data_url) or "" | |
dl_dir = os.path.join(dl_dir, f"source_code/{self.config.name}") | |
return [ | |
datasets.SplitGenerator( | |
name=datasets.Split.TRAIN, | |
gen_kwargs={ | |
"filepath": os.path.join(dl_dir, f"train.txt"), | |
}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.VALIDATION, | |
gen_kwargs={ | |
"filepath": os.path.join(dl_dir, f"valid.txt"), | |
}, | |
), | |
datasets.SplitGenerator( | |
name=datasets.Split.TEST, | |
gen_kwargs={ | |
"filepath": os.path.join(dl_dir, f"test.txt"), | |
}, | |
), | |
] | |
def _generate_examples(self, filepath): | |
"""This function returns the examples in the raw (text) form.""" | |
with open(filepath, 'r', encoding="utf-8") as f: | |
for idx, row in enumerate(f): | |
if row.strip(): | |
yield idx, {"text": row} | |
else: | |
yield idx, {"text": ""} | |