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from typing import List |
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import datasets |
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from .common import Child |
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from .generated_definitions import DEFINITIONS |
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_DESCRIPTION = """The dataset we use is crawled and filtered from Microsoft Documentation, whose document located at https://github.com/MicrosoftDocs/.""" |
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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 CodeXGlueTtTextToTextImpl(Child): |
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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"), |
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"source": datasets.Value("string"), |
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"target": datasets.Value("string"), |
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} |
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_SUPERVISED_KEYS = ["target"] |
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KEYS = ["source", "target"] |
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SPLITS = {"train": datasets.Split.TRAIN, "dev": datasets.Split.VALIDATION, "test": datasets.Split.TEST} |
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def generate_urls(self, split_name): |
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lang_pair = self.info["parameters"]["natural_language_pair"] |
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for i, lang in enumerate(lang_pair.split("-")): |
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yield self.KEYS[i], f"{split_name}/{lang_pair}.{split_name}.{lang}" |
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def _generate_examples(self, split_name, file_paths): |
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print(file_paths) |
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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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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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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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"CodeXGlueTtTextToText": CodeXGlueTtTextToTextImpl, |
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} |
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class CodeXGlueTtTextToText(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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