Delete ClassEval.py

ClassEval.py

@@ -1,104 +0,0 @@
-import json
-import datasets
-
-_DESCRIPTION = """\
-FudanSELab ClassEval
-"""
-_URL = "ClassEval_data.json"
-
-_CITATION = """\
-@misc{du2023classeval,
-      title={ClassEval: A Manually-Crafted Benchmark for Evaluating LLMs on Class-level Code Generation}, 
-      author={Xueying Du and Mingwei Liu and Kaixin Wang and Hanlin Wang and Junwei Liu and Yixuan Chen and Jiayi Feng and Chaofeng Sha and Xin Peng and Yiling Lou},
-      year={2023},
-      eprint={2308.01861},
-      archivePrefix={arXiv},
-      primaryClass={cs.CL}
-}"""
-
-_HOMEPAGE = "https://github.com/FudanSELab/ClassEval"
-
-_LICENSE = "MIT"
-
-class ClassEval(datasets.GeneratorBasedBuilder):
-    VERSION = datasets.Version("1.0.0")
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            name="class_eval",
-            version=datasets.Version("1.0.0"),
-            description=_DESCRIPTION,
-        )
-    ]
-
-    def _info(self):
-        method_feature = datasets.Features(
-            {
-                "method_name": datasets.Value("string"),
-                "method_description": datasets.Value("string"),
-                "test_class": datasets.Value("string"),
-                "test_code": datasets.Value("string"),
-                "solution_code": datasets.Value("string"),
-                "dependencies": {
-                    "Standalone": datasets.Value("bool"),
-                    "lib_dependencies": datasets.Sequence(datasets.Value("string")),
-                    "field_dependencies": datasets.Sequence(datasets.Value("string")),
-                    "method_dependencies": datasets.Sequence(datasets.Value("string")),
-                }
-            }
-        )
-        features = datasets.Features(
-            {
-                "task_id": datasets.Value("string"),
-                "skeleton": datasets.Value("string"),
-                "test": datasets.Value("string"),
-                "solution_code": datasets.Value("string"),
-                "import_statement": [datasets.Value("string")],
-                "class_description": datasets.Value("string"),
-                "class_name": datasets.Value("string"),
-                "test_classes": datasets.Sequence(datasets.Value("string")),
-                "class_constructor": datasets.Value("string"),
-                "fields": datasets.Sequence(datasets.Value("string")),
-                "methods_info": [method_feature],
-            }
-        )
-
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            supervised_keys=None,
-            homepage=_HOMEPAGE,
-            license=_LICENSE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Returns SplitGenerators."""
-        data_dir = dl_manager.download(_URL)
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
-                gen_kwargs={
-                    "filepath": data_dir,
-                },
-            )
-        ]
-
-    def _generate_examples(self, filepath):
-        key = 0
-        with open(filepath, encoding = 'utf-8') as f:
-            cont = json.load(f)
-            for row in cont:
-                yield key, {
-                    "task_id": row["task_id"],
-                    "skeleton": row["skeleton"],
-                    "test": row["test"],
-                    "solution_code": row["solution_code"],
-                    "import_statement": row["import_statement"],
-                    "class_description": row["class_description"],
-                    "class_name": row["class_name"],
-                    "test_classes": row["test_classes"],
-                    "class_constructor": row["class_constructor"],
-                    "fields": row["fields"],
-                    "methods_info": row["methods_info"],
-                }
-                key += 1