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