# coding=utf-8 # Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """HumanEval-X dataset.""" import json import datasets _DESCRIPTION = """ HumanEval-X is a benchmark for the evaluation of the multilingual ability of code generative models. \ It consists of 820 high-quality human-crafted data samples (each with test cases) in Python, C++, Java, JavaScript, and Go, and can be used for various tasks. """ _HOMEPAGE = "https://github.com/THUDM/CodeGeeX" def get_url(name): url = f"data/{name}/data/humaneval.jsonl" return url def split_generator(dl_manager, name): downloaded_files = dl_manager.download(get_url(name)) return [ datasets.SplitGenerator( name=datasets.Split.TEST, gen_kwargs={ "filepath": downloaded_files, }, ) ] class HumanEvalXConfig(datasets.BuilderConfig): """BuilderConfig """ def __init__(self, name, description, features, **kwargs): super(HumanEvalXConfig, self).__init__(version=datasets.Version("1.0.0", ""), **kwargs) self.name = name self.description = description self.features = features class HumanEvalX(datasets.GeneratorBasedBuilder): VERSION = datasets.Version("1.0.0") BUILDER_CONFIGS = [ HumanEvalXConfig( name="python", description="Python HumanEval", features=["task_id", "prompt", "declaration", "canonical_solution", "test", "example_test"] ), HumanEvalXConfig( name="cpp", description="C++ HumanEval", features=["task_id", "prompt", "declaration", "canonical_solution", "test", "example_test"] ), HumanEvalXConfig( name="go", description="Go HumanEval", features=["task_id", "prompt", "declaration", "canonical_solution", "test", "example_test"] ), HumanEvalXConfig( name="java", description="Java HumanEval", features=["task_id", "prompt", "declaration", "canonical_solution", "test", "example_test"] ), HumanEvalXConfig( name="js", description="JavaScript HumanEval", features=["task_id", "prompt", "declaration", "canonical_solution", "test", "example_test"] ), ] DEFAULT_CONFIG_NAME = "python" def _info(self): return datasets.DatasetInfo( description=_DESCRIPTION, features=datasets.Features({"task_id": datasets.Value("string"), "prompt": datasets.Value("string"), "declaration": datasets.Value("string"), "canonical_solution": datasets.Value("string"), "test": datasets.Value("string"), "example_test": datasets.Value("string"), }), homepage=_HOMEPAGE, ) def _split_generators(self, dl_manager): if self.config.name == "python": return split_generator(dl_manager, self.config.name) elif self.config.name == "cpp": return split_generator(dl_manager, self.config.name) elif self.config.name == "go": return split_generator(dl_manager, self.config.name) elif self.config.name == "java": return split_generator(dl_manager, self.config.name) elif self.config.name == "js": return split_generator(dl_manager, self.config.name) def _generate_examples(self, filepath): key = 0 with open(filepath) as f: for line in f: row = json.loads(line) key += 1 yield key, { "task_id": row["task_id"], "prompt": row["prompt"], "declaration": row["declaration"], "canonical_solution": row["canonical_solution"], "test": row["test"], "example_test": row["example_test"], } key += 1