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Upload MATH-lighteval.py

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+ """Mathematics Aptitude Test of Heuristics (MATH) dataset, lighteval format with correct builder configs."""
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+
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+ import json
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+ import os
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+
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+
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+ from datasets import load_dataset, Dataset, DatasetDict, GeneratorBasedBuilder, BuilderConfig, DatasetInfo, Value, Features, Split, SplitGenerator, Version
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+
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+
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+ _CITATION = """\
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+ @article{hendrycksmath2021,
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+ title={Measuring Mathematical Problem Solving With the MATH Dataset},
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+ author={Dan Hendrycks
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+ and Collin Burns
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+ and Saurav Kadavath
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+ and Akul Arora
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+ and Steven Basart
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+ and Eric Tang
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+ and Dawn Song
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+ and Jacob Steinhardt},
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+ journal={arXiv preprint arXiv:2103.03874},
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+ year={2021}
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+ }
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+ """
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+
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+
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+ _DESCRIPTION = """\
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+ The Mathematics Aptitude Test of Heuristics (MATH) dataset consists of problems
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+ from mathematics competitions, including the AMC 10, AMC 12, AIME, and more.
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+ Each problem in MATH has a full step-by-step solution, which can be used to teach
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+ models to generate answer derivations and explanations. This version of the dataset
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+ includes appropriate builder configs s.t. it can be used as a drop-in replacement
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+ for the now missing lighteval/MATH dataset.
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+ """
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+
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+
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+ _HOMEPAGE = "https://github.com/hendrycks/math"
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+
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+
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+ _LICENSE = "https://github.com/hendrycks/math/blob/main/LICENSE"
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+
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+
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+ # Original data URL: "https://people.eecs.berkeley.edu/~hendrycks/MATH.tar"
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+ _URL = "data/MATH.zip"
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+
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+
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+ class FilteredTypeConfig(BuilderConfig):
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+ def __init__(self, type_value, type_name, **kwargs):
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+ super().__init__(**kwargs)
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+ self.type_value = type_value
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+ self.type_name = type_name
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+
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+ class FilteredTypeDatasetBuilder(GeneratorBasedBuilder):
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+ """Mathematics Aptitude Test of Heuristics (MATH) dataset."""
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+
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+ VERSION = Version("1.0.0")
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+
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+ BUILDER_CONFIGS = [FilteredTypeConfig(
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+ name="default",
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+ version="1.0.0",
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+ description=f"default builder config",
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+ type_name="default", # for builder config
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+ type_value="default", # in original dataset
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+ )] + [
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+ FilteredTypeConfig(
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+ name=type_name,
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+ version="1.0.0",
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+ description=f"Dataset filtered by type: {type_value}",
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+ type_name=type_name, # for builder config
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+ type_value=type_value, # in original dataset
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+ )
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+ for type_name, type_value in [("algebra", "Algebra"), ("counting_and_probability", "Counting & Probability"), ("geometry", "Geometry"), ("intermediate_algebra", "Intermediate Algebra"), ("number_theory", "Number Theory"), ("prealgebra", "Prealgebra"), ("precalculus", "Precalculus")]
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+ ]
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+
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+ def _info(self):
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+ return DatasetInfo(
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+ description=_DESCRIPTION,
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+ features=Features({
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+ "problem": Value("string"),
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+ "level": Value("string"),
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+ "solution": Value("string"),
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+ "type": Value("string"),
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+ }),
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+ supervised_keys=None,
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+ homepage=_HOMEPAGE,
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+ license=_LICENSE,
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+ citation=_CITATION
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+ )
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+
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+ def _split_generators(self, dl_manager):
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+ """Returns SplitGenerators."""
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+ download_dir = dl_manager.download_and_extract(_URL)
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+ return [
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+ SplitGenerator(
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+ name=Split.TRAIN,
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+ gen_kwargs={"data_dir": dl_manager.iter_files(os.path.join(download_dir, "MATH", "train"))},
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+ ),
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+ SplitGenerator(
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+ name=Split.TEST,
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+ gen_kwargs={"data_dir": dl_manager.iter_files(os.path.join(download_dir, "MATH", "test"))},
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+ ),
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+ ]
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+
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+ def _generate_examples(self, data_dir):
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+ type_value = self.config.type_value # Access the type value for the current config
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+
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+ """Yields examples as (key, example) tuples. Filters by type if appropriate builder config is given."""
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+ for id_, filepath in enumerate(data_dir):
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+ with open(filepath, "rb") as fin:
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+ example = json.load(fin)
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+ if type_value == "default" or example["type"] == type_value:
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+ yield id_, example
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+
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+