Datasets:
Tasks:
Translation
Modalities:
Text
Formats:
parquet
Languages:
code
Size:
10K - 100K
ArXiv:
Tags:
code-to-code
License:
Commit
•
946dd8d
1
Parent(s):
f18c108
Delete loading script
Browse files
code_x_glue_cc_code_to_code_trans.py
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from typing import List
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import datasets
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from .common import TrainValidTestChild
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from .generated_definitions import DEFINITIONS
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_DESCRIPTION = """The dataset is collected from several public repos, including Lucene(http://lucene.apache.org/), POI(http://poi.apache.org/), JGit(https://github.com/eclipse/jgit/) and Antlr(https://github.com/antlr/).
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We collect both the Java and C# versions of the codes and find the parallel functions. After removing duplicates and functions with the empty body, we split the whole dataset into training, validation and test sets."""
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_CITATION = """@article{DBLP:journals/corr/abs-2102-04664,
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author = {Shuai Lu and
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Daya Guo and
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Shuo Ren and
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Junjie Huang and
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Alexey Svyatkovskiy and
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Ambrosio Blanco and
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Colin B. Clement and
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Dawn Drain and
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Daxin Jiang and
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Duyu Tang and
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Ge Li and
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Lidong Zhou and
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Linjun Shou and
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Long Zhou and
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Michele Tufano and
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Ming Gong and
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Ming Zhou and
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Nan Duan and
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Neel Sundaresan and
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Shao Kun Deng and
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Shengyu Fu and
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Shujie Liu},
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title = {CodeXGLUE: {A} Machine Learning Benchmark Dataset for Code Understanding
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and Generation},
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journal = {CoRR},
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volume = {abs/2102.04664},
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year = {2021}
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}"""
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class CodeXGlueCcCodeToCodeTransImpl(TrainValidTestChild):
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_DESCRIPTION = _DESCRIPTION
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_CITATION = _CITATION
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_FEATURES = {
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"id": datasets.Value("int32"), # Index of the sample
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"java": datasets.Value("string"), # The java version of the code
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"cs": datasets.Value("string"), # The C# version of the code
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}
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def generate_urls(self, split_name):
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for key in "cs", "java":
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yield key, f"{split_name}.java-cs.txt.{key}"
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def _generate_examples(self, split_name, file_paths):
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"""This function returns the examples in the raw (text) form."""
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# Open each file (one for java, and one for c#)
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files = {k: open(file_paths[k], encoding="utf-8") for k in file_paths}
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id_ = 0
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while True:
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# Read a single line from each file
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entries = {k: files[k].readline() for k in file_paths}
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empty = self.check_empty(entries)
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if empty:
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# We are done: end of files
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return
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entries["id"] = id_
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yield id_, entries
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id_ += 1
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CLASS_MAPPING = {
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"CodeXGlueCcCodeToCodeTrans": CodeXGlueCcCodeToCodeTransImpl,
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}
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class CodeXGlueCcCodeToCodeTrans(datasets.GeneratorBasedBuilder):
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BUILDER_CONFIG_CLASS = datasets.BuilderConfig
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(name=name, description=info["description"]) for name, info in DEFINITIONS.items()
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]
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def _info(self):
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name = self.config.name
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info = DEFINITIONS[name]
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if info["class_name"] in CLASS_MAPPING:
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self.child = CLASS_MAPPING[info["class_name"]](info)
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else:
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raise RuntimeError(f"Unknown python class for dataset configuration {name}")
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ret = self.child._info()
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return ret
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def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]:
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return self.child._split_generators(dl_manager=dl_manager)
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def _generate_examples(self, split_name, file_paths):
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return self.child._generate_examples(split_name, file_paths)
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