MultiPL-E v3 prompts and tests

MultiPL-E.py

@@ -1,116 +0,0 @@
-import json
-import datasets
-from pathlib import Path
-
-logger = datasets.logging.get_logger(__name__)
-
-_CITATION = """\
-@article{cassano:multipl-e,
-  author = {Cassano, Federico and Gouwar, John and Nguyen, Daniel and Nguyen, Sydney and
-            Phipps-Costin, Luna and Pinckney, Donald and Yee, Ming-Ho and Zi, Yangtian and
-            Anderson, Carolyn Jane and Feldman, Molly Q and Guha, Arjun and
-            Greenberg, Michael and Jangda, Abhinav},
-  title = {{MultiPL-E}: A Scalable and Polyglot Approach to Benchmarking Neural Code Generation},
-  journal = "{IEEE} Transactions of Software Engineering (TSE)",
-  year = 2023
-}"""
-
-_DESCRIPTION = """\
-MultiPL-E is a dataset for evaluating large language models for code \
-generation that supports 18 programming languages. It takes the OpenAI \
-"HumanEval" and the MBPP Python benchmarks and uses little compilers to \
-translate them to other languages. It is easy to add support for new languages \
-and benchmarks.
-"""
-
-_SRCDATA = [ "humaneval", "mbpp" ]
-
-_LANGUAGES = [ 
-    "cpp", "cs", "d", "go", "java", "jl", "js", "lua", "php", "pl", "py", "r", 
-    "rb", "rkt", "rs", "scala", "sh", "swift", "ts"
-]
-
-_VARIATIONS = [ "keep", "transform", "reworded", "remove" ]
-
-class MultiPLEBuilderConfig(datasets.BuilderConfig):
-    """BuilderConfig for MultiPLEBuilderConfig."""
-
-    def __init__(
-        self,
-        srcdata,
-        language,
-        variation,
-        **kwargs,
-    ):
-        self.language = language
-        self.variation = variation
-        self.srcdata = srcdata
-        name = f"{srcdata}-{language}"
-        if variation != "reworded":
-            name = f"{name}-{variation}"
-        kwargs["name"] = name
-        super(MultiPLEBuilderConfig, self).__init__(**kwargs)
-
-def _is_interesting(srcdata: str, variation: str):
-    if srcdata == "humaneval":
-        return True
-    if srcdata == "mbpp":
-        # MBPP does not have doctests, so these are the only interesting
-        # variations
-        return variation in [ "keep", "reworded" ]
-
-class MultiPLE(datasets.GeneratorBasedBuilder):
-    BUILDER_CONFIG_CLASS = MultiPLEBuilderConfig
-
-    BUILDER_CONFIGS = [
-        MultiPLEBuilderConfig(
-            srcdata=srcdata,
-            language=language,
-            variation=variation,
-            version=datasets.Version("2.1.0"))
-        for srcdata in _SRCDATA
-        for language in _LANGUAGES 
-        for variation in _VARIATIONS
-        if _is_interesting(srcdata, variation)
-    ]
-
-    DEFAULT_CONFIG_NAME = "humaneval-cpp"
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            license="MIT",
-            features=datasets.Features({
-                "name": datasets.Value("string"),
-                "language": datasets.Value("string"),
-                "prompt": datasets.Value("string"),
-                "doctests": datasets.Value("string"),
-                "original": datasets.Value("string"),
-                "prompt_terminology": datasets.Value("string"),
-                "tests": datasets.Value("string"),
-                "stop_tokens": datasets.features.Sequence(datasets.Value("string")),
-            }),
-            supervised_keys=None,
-            homepage="https://nuprl.github.io/MultiPL-E/",
-            citation=_CITATION,
-            task_templates=[]
-        )
-
-    def _split_generators(self, dl_manager: datasets.DownloadManager):
-        files = dl_manager.download(
-            f"https://raw.githubusercontent.com/nuprl/MultiPL-E/11b407bd2dd98c8204afea4d20043faf2145c20c/prompts/{self.config.srcdata}-{self.config.language}-{self.config.variation}.json"
-        )
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "filepath": files,
-                }
-            )
-        ]
-
-    def _generate_examples(self, filepath):
-        with open(filepath, encoding="utf-8") as f:
-            data = json.load(f)
-            for id_, row in enumerate(data):
-                yield id_, row

how_to_update.txt

@@ -1,6 +0,0 @@
-To update this dataset:
-
-1. Edit the commit hash in MultiPL-E.py (line 106)
-
-2. Run `datasets-cli test MultiPL-E.py --save_info --all_configs` to regenerate
-   `dataset_infos.json`.

humaneval-clj/test-00000-of-00001.parquet

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