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import json, datasets |
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from datasets import Features, Value, Sequence, Split, SplitGenerator |
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_CITATION = "" |
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_DESCRIPTION = "BlueMO dataset." |
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class BlueMO(datasets.GeneratorBasedBuilder): |
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BUILDER_CONFIGS = [ |
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datasets.BuilderConfig(name="default"), |
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datasets.BuilderConfig(name="proof"), |
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datasets.BuilderConfig(name="calculation"), |
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datasets.BuilderConfig(name="mathtext"), |
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] |
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def _info(self): |
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if self.config.name in ("proof", "calculation", "default"): |
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feats = Features({ |
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"source_file": Value("string"), |
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"problem_type": Value("string"), |
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"problem": Value("string"), |
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"solution": Value("string"), |
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"remark": Value("string"), |
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"figures": Sequence(Value("string")), |
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}) |
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else: |
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feats = Features({ |
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"source_file": Value("string"), |
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"text": Value("string"), |
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"figures": Sequence(Value("string")), |
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}) |
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return datasets.DatasetInfo(description=_DESCRIPTION, citation=_CITATION, features=feats) |
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def _split_generators(self, dl_manager): |
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if self.config.name == "proof": |
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paths = dl_manager.iter_files(["processed_dataset/proof"]) |
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elif self.config.name == "calculation": |
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paths = dl_manager.iter_files(["processed_dataset/calculation"]) |
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elif self.config.name == "mathtext": |
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paths = dl_manager.iter_files(["processed_dataset/text"]) |
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else: |
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paths = dl_manager.iter_files(["processed_dataset/proof", "processed_dataset/calculation"]) |
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return [SplitGenerator(name=Split.TRAIN, gen_kwargs={"paths": list(paths)})] |
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def _generate_examples(self, paths): |
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for i, p in enumerate(sorted(paths)): |
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with open(p, "r", encoding="utf-8") as f: |
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obj = json.load(f) |
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if "figures" in obj and obj["figures"] is None: |
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obj["figures"] = [] |
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if "figures" in obj: |
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obj["figures"] = [str(x) for x in (obj["figures"] or [])] |
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yield str(i), obj |
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