Datasets:
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from typing import List
import datasets
from .common import Child
from .generated_definitions import DEFINITIONS
_DESCRIPTION = """The dataset we use is crawled and filtered from Microsoft Documentation, whose document located at https://github.com/MicrosoftDocs/."""
_CITATION = """@article{DBLP:journals/corr/abs-2102-04664,
author = {Shuai Lu and
Daya Guo and
Shuo Ren and
Junjie Huang and
Alexey Svyatkovskiy and
Ambrosio Blanco and
Colin B. Clement and
Dawn Drain and
Daxin Jiang and
Duyu Tang and
Ge Li and
Lidong Zhou and
Linjun Shou and
Long Zhou and
Michele Tufano and
Ming Gong and
Ming Zhou and
Nan Duan and
Neel Sundaresan and
Shao Kun Deng and
Shengyu Fu and
Shujie Liu},
title = {CodeXGLUE: {A} Machine Learning Benchmark Dataset for Code Understanding
and Generation},
journal = {CoRR},
volume = {abs/2102.04664},
year = {2021}
}"""
class CodeXGlueTtTextToTextImpl(Child):
_DESCRIPTION = _DESCRIPTION
_CITATION = _CITATION
_FEATURES = {
"id": datasets.Value("int32"), # The index of the sample
"source": datasets.Value("string"), # The source language version of the text
"target": datasets.Value("string"), # The target language version of the text
}
_SUPERVISED_KEYS = ["target"]
KEYS = ["source", "target"]
SPLITS = {"train": datasets.Split.TRAIN, "dev": datasets.Split.VALIDATION, "test": datasets.Split.TEST}
def generate_urls(self, split_name):
lang_pair = self.info["parameters"]["natural_language_pair"]
for i, lang in enumerate(lang_pair.split("-")):
yield self.KEYS[i], f"{split_name}/{lang_pair}.{split_name}.{lang}"
def _generate_examples(self, split_name, file_paths):
print(file_paths)
# Open each file (one for source language and the other for target language)
files = {k: open(file_paths[k], encoding="utf-8") for k in file_paths}
id_ = 0
while True:
# Read a single line from each file
entries = {k: files[k].readline() for k in file_paths}
empty = self.check_empty(entries)
if empty:
# We are done: end of files
return
entries["id"] = id_
yield id_, entries
id_ += 1
CLASS_MAPPING = {
"CodeXGlueTtTextToText": CodeXGlueTtTextToTextImpl,
}
class CodeXGlueTtTextToText(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)
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