Create mxeval.py

mxeval.py

@@ -0,0 +1,323 @@
+import json
+import os
+import requests
+import datasets
+
+import os
+from collections import defaultdict
+
+_CITATION = """\
+@article{mbxp_athiwaratkun2022,
+  title = {Multi-lingual Evaluation of Code Generation Models},
+  author = {Athiwaratkun, Ben and
+   Gouda, Sanjay Krishna and
+   Wang, Zijian and
+   Li, Xiaopeng and
+   Tian, Yuchen and
+   Tan, Ming
+   and Ahmad, Wasi Uddin and
+   Wang, Shiqi and
+   Sun, Qing and
+   Shang, Mingyue and
+   Gonugondla, Sujan Kumar and
+   Ding, Hantian and
+   Kumar, Varun and
+   Fulton, Nathan and
+   Farahani, Arash and
+   Jain, Siddhartha and
+   Giaquinto, Robert and
+   Qian, Haifeng and
+   Ramanathan, Murali Krishna and
+   Nallapati, Ramesh and
+   Ray, Baishakhi and
+   Bhatia, Parminder and
+   Sengupta, Sudipta and
+   Roth, Dan and
+   Xiang, Bing},
+  doi = {10.48550/ARXIV.2210.14868},
+  url = {https://arxiv.org/abs/2210.14868},
+  keywords = {Machine Learning (cs.LG), Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  publisher = {arXiv},
+  year = {2022},
+  copyright = {Creative Commons Attribution 4.0 International}
+}"""
+
+VERSION=f"1.1.0"
+
+_HOMEPAGE = "https://github.com/amazon-science/mxeval"
+
+_LICENSE = "Apache License 2.0"
+
+_DESCRIPTION = """\
+A collection of execution-based multi-lingual benchmark for code generation.
+"""
+
+_LICENSES = defaultdict(lambda: _LICENSE)
+_LICENSES["humaneval_python"] = "MIT License"
+_LICENSES["mbxp_python"] = "CC-BY-4.0"
+
+_CITATIONS = defaultdict(lambda: _CITATION)
+
+_CITATIONS["multi-humaneval"] = """\
+@article{mbxp_athiwaratkun2022,
+  title = {Multi-lingual Evaluation of Code Generation Models},
+  author = {Athiwaratkun, Ben and
+   Gouda, Sanjay Krishna and
+   Wang, Zijian and
+   Li, Xiaopeng and
+   Tian, Yuchen and
+   Tan, Ming
+   and Ahmad, Wasi Uddin and
+   Wang, Shiqi and
+   Sun, Qing and
+   Shang, Mingyue and
+   Gonugondla, Sujan Kumar and
+   Ding, Hantian and
+   Kumar, Varun and
+   Fulton, Nathan and
+   Farahani, Arash and
+   Jain, Siddhartha and
+   Giaquinto, Robert and
+   Qian, Haifeng and
+   Ramanathan, Murali Krishna and
+   Nallapati, Ramesh and
+   Ray, Baishakhi and
+   Bhatia, Parminder and
+   Sengupta, Sudipta and
+   Roth, Dan and
+   Xiang, Bing},
+  doi = {10.48550/ARXIV.2210.14868},
+  url = {https://arxiv.org/abs/2210.14868},
+  keywords = {Machine Learning (cs.LG), Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  publisher = {arXiv},
+  year = {2022},
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+@misc{chen2021evaluating,
+      title={Evaluating Large Language Models Trained on Code},
+      author={Mark Chen and Jerry Tworek and Heewoo Jun and Qiming Yuan and Henrique Ponde de Oliveira Pinto and Jared Kaplan and Harri Edwards and Yuri Burda and Nicholas Joseph and Greg Brockman and Alex Ray and Raul Puri and Gretchen Krueger and Michael Petrov and Heidy Khlaaf and Girish Sastry and Pamela Mishkin and Brooke Chan and Scott Gray and Nick Ryder and Mikhail Pavlov and Alethea Power and Lukasz Kaiser and Mohammad Bavarian and Clemens Winter and Philippe Tillet and Felipe Petroski Such and Dave Cummings and Matthias Plappert and Fotios Chantzis and Elizabeth Barnes and Ariel Herbert-Voss and William Hebgen Guss and Alex Nichol and Alex Paino and Nikolas Tezak and Jie Tang and Igor Babuschkin and Suchir Balaji and Shantanu Jain and William Saunders and Christopher Hesse and Andrew N. Carr and Jan Leike and Josh Achiam and Vedant Misra and Evan Morikawa and Alec Radford and Matthew Knight and Miles Brundage and Mira Murati and Katie Mayer and Peter Welinder and Bob McGrew and Dario Amodei and Sam McCandlish and Ilya Sutskever and Wojciech Zaremba},
+      year={2021},
+      eprint={2107.03374},
+      archivePrefix={arXiv},
+      primaryClass={cs.LG}
+}"""
+
+_CITATIONS["mbxp"] = """\
+@article{mbxp_athiwaratkun2022,
+  title = {Multi-lingual Evaluation of Code Generation Models},
+  author = {Athiwaratkun, Ben and
+   Gouda, Sanjay Krishna and
+   Wang, Zijian and
+   Li, Xiaopeng and
+   Tian, Yuchen and
+   Tan, Ming
+   and Ahmad, Wasi Uddin and
+   Wang, Shiqi and
+   Sun, Qing and
+   Shang, Mingyue and
+   Gonugondla, Sujan Kumar and
+   Ding, Hantian and
+   Kumar, Varun and
+   Fulton, Nathan and
+   Farahani, Arash and
+   Jain, Siddhartha and
+   Giaquinto, Robert and
+   Qian, Haifeng and
+   Ramanathan, Murali Krishna and
+   Nallapati, Ramesh and
+   Ray, Baishakhi and
+   Bhatia, Parminder and
+   Sengupta, Sudipta and
+   Roth, Dan and
+   Xiang, Bing},
+  doi = {10.48550/ARXIV.2210.14868},
+  url = {https://arxiv.org/abs/2210.14868},
+  keywords = {Machine Learning (cs.LG), Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  publisher = {arXiv},
+  year = {2022},
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+@article{austin2021program,
+  title={Program Synthesis with Large Language Models},
+  author={Austin, Jacob and Odena, Augustus and Nye, Maxwell and Bosma, Maarten and Michalewski, Henryk and Dohan, David and Jiang, Ellen and Cai, Carrie and Terry, Michael and Le, Quoc and others},
+  journal={arXiv preprint arXiv:2108.07732},
+  year={2021}
+}"""
+
+_CITATIONS["mathqa-x"] = """\
+@article{mbxp_athiwaratkun2022,
+  title = {Multi-lingual Evaluation of Code Generation Models},
+  author = {Athiwaratkun, Ben and
+   Gouda, Sanjay Krishna and
+   Wang, Zijian and
+   Li, Xiaopeng and
+   Tian, Yuchen and
+   Tan, Ming
+   and Ahmad, Wasi Uddin and
+   Wang, Shiqi and
+   Sun, Qing and
+   Shang, Mingyue and
+   Gonugondla, Sujan Kumar and
+   Ding, Hantian and
+   Kumar, Varun and
+   Fulton, Nathan and
+   Farahani, Arash and
+   Jain, Siddhartha and
+   Giaquinto, Robert and
+   Qian, Haifeng and
+   Ramanathan, Murali Krishna and
+   Nallapati, Ramesh and
+   Ray, Baishakhi and
+   Bhatia, Parminder and
+   Sengupta, Sudipta and
+   Roth, Dan and
+   Xiang, Bing},
+  doi = {10.48550/ARXIV.2210.14868},
+  url = {https://arxiv.org/abs/2210.14868},
+  keywords = {Machine Learning (cs.LG), Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
+  publisher = {arXiv},
+  year = {2022},
+  copyright = {Creative Commons Attribution 4.0 International}
+}
+@inproceedings{amini-etal-2019-mathqa,
+    title={MathQA: Towards Interpretable Math Word Problem Solving with Operation-Based Formalisms},
+    author={Amini, Aida  and
+      Gabriel, Saadia  and
+      Lin, Shanchuan  and
+      Koncel-Kedziorski, Rik  and
+      Choi, Yejin  and
+      Hajishirzi, Hannaneh},
+    booktitle={Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)},
+    month={jun},
+    year= {2019},
+    address = {Minneapolis, Minnesota},
+    publisher = {Association for Computational Linguistics},
+    url={https://aclanthology.org/N19-1245}
+    doi={10.18653/v1/N19-1245},
+    pages={2357--2367},
+}
+"""
+
+_DATASET_NAME_MAPPER = {
+    "mbxp": "mbxp",
+    "multi-humaneval": "multilingual_humaneval",
+    "mathqa-x": "multilingual_mathqa"
+}
+
+_GITHUB_ROOT = "https://raw.githubusercontent.com/amazon-science/mxeval/main/data/"
+
+
+def get_metadata_dict(dataset):
+    metadata_dict_path = requests.get(os.path.join(_GITHUB_ROOT, dataset, "metadata.json"))
+    metadata = json.loads(metadata_dict_path.text)
+    return metadata
+
+
+MBXP_LANGUAGES = get_metadata_dict("mbxp")
+
+MATHQA_LANGUAGES = get_metadata_dict("multilingual_mathqa")
+
+HUMANEVAL_LANGUAGES = get_metadata_dict("multilingual_humaneval")
+
+_DATASET_LANGS = {
+    "multi-humaneval": HUMANEVAL_LANGUAGES,
+    "mathqa-x": MATHQA_LANGUAGES,
+    "mbxp": MBXP_LANGUAGES
+}
+
+_INTERNAL_DATASET_NAMES = {
+    "multi-humaneval": "multilingual_humaneval",
+    "mathqa-x": "multilingual_mathqa",
+    "mbxp": "mbxp"
+}
+
+_URL_DICT = {
+    f"{dataset.lower()}_{language.lower()}": os.path.join(
+        _GITHUB_ROOT,
+        _INTERNAL_DATASET_NAMES[dataset],
+        _DATASET_LANGS[dataset][language]
+        )
+    for dataset, languages in _DATASET_LANGS.items() for language in languages
+}
+
+
+class MxEvalConfig(datasets.BuilderConfig):
+    """BuilderConfig for MxEval."""
+
+    def __init__(
+        self,
+        dataset,
+        citation,
+        version,
+        **kwargs,
+    ):
+        super(MxEvalConfig, self).__init__(version=datasets.Version(f"{version}", ""), **kwargs)
+        self.dataset_name = dataset
+        self.data_dir = os.path.join(_GITHUB_ROOT, dataset)
+        self.citation = citation
+
+
+class MxEval(datasets.GeneratorBasedBuilder):
+    """MxEval: An execution-based multiLingual benchmark for code generation."""
+
+    BUILDER_CONFIGS = [
+        MxEvalConfig(
+            name=f"{dataset}",
+            version=VERSION,
+            citation=_CITATIONS[f"{dataset}"],
+            dataset=_DATASET_NAME_MAPPER[dataset],
+            description=f"Benchmark for {dataset}",
+        ) for dataset in _DATASET_LANGS
+    ]
+
+    def _info(self):
+        self.build_name = self.name
+        features = datasets.Features(
+            {
+                "task_id": datasets.Value("string"),
+                "language": datasets.Value("string"),
+                "prompt": datasets.Value("string"),
+                "description": datasets.Value("string"),
+                "test": datasets.Value("string"),
+                "entry_point": datasets.Value("string"),
+                "canonical_solution": datasets.Value("string"),
+            }
+        )
+
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            supervised_keys=None,
+            homepage=_HOMEPAGE,
+            license=_LICENSES[self.config.name],
+            citation=_CITATIONS[self.config.name],
+        )
+
+
+    def _split_generators(
+            self, dl_manager
+    ):
+        """Returns SplitGenerators."""
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split(lang),
+                gen_kwargs={
+                    "filepath": dl_manager.download_and_extract(
+                        url_or_urls=_URL_DICT[f"{self.config.name}_{lang}"]
+                    ),
+                },
+            ) for lang in _DATASET_LANGS[self.config.name]
+        ]
+
+    
+    def _generate_examples(self, filepath):
+        """Yields examples."""
+        with open(filepath) as file:
+            data = []
+            for line in file:
+                jd = json.loads(line)
+                data.append(jd)
+            id_ = 0
+            for sample in data:
+                yield id_, sample
+                id_ += 1