Upload odex.py

README.md

@@ -16,6 +16,12 @@ __ODEX__ is an Open-Domain EXecution-based NL-to-Code generation data benchmark.
 It contains 945 samples with a total of 1,707 human-written test cases, covering intents in four different natural languages --  439 in English, 90 in Spanish, 164 in Japanese, and 252 in Russian.
 
 
+You can load the dataset by specifying a subset from *en, es, ja, ru* (by default the english subset *en* is loaded):
+```python
+from datasets import load_dataset
+
+ds = load_dataset("neulab/odex", "ja", split="test")
+```
 
 If you find our dataset useful, please cite the paper
 

odex.py

@@ -0,0 +1,82 @@
+"""Odex dataset."""
+
+import json
+import datasets
+
+
+_CITATION = """\
+@article{wang2022execution,
+  title={Execution-Based Evaluation for Open-Domain Code Generation},
+  author={Wang, Zhiruo and Zhou, Shuyan and Fried, Daniel and Neubig, Graham},
+  journal={arXiv preprint arXiv:2212.10481},
+  year={2022}
+}
+"""
+
+_DESCRIPTION = """\
+ODEX is an Open-Domain EXecution-based NL-to-Code generation data benchmark. 
+It contains 945 samples with a total of 1,707 human-written test cases, 
+covering intents in four different natural languages -- 439 in English, 90 in Spanish, 164 in Japanese, and 252 in Russian.
+"""
+
+_HOMEPAGE = "https://github.com/zorazrw/odex"
+_URLs = {
+    "en": "en_test.jsonl",
+    "es": "es_test.jsonl",
+    "ja": "ja_test.jsonl",
+    "ru": "ru_test.jsonl",
+}
+
+class Odex(datasets.GeneratorBasedBuilder):
+    """ODEX Code dataset."""
+
+    VERSION = datasets.Version("1.0.0")
+
+
+    BUILDER_CONFIGS = [
+        datasets.BuilderConfig(
+            name=lang,
+            version=datasets.Version("1.0.0"),
+            description=_DESCRIPTION,
+        ) for lang in _URLs.keys()
+    ]
+
+    DEFAULT_CONFIG_NAME = "en"
+    
+    
+    def _info(self):
+        features = datasets.Features({"task_id": datasets.Value("int64"),
+                                        "prompt": datasets.Value("string"),
+                                        "suffix": datasets.Value("string"),
+                                        "canonical_solution": datasets.Value("string"),
+                                        "test_start": datasets.Value("string"),
+                                        "test": datasets.Sequence(datasets.Value("string")),
+                                        "entry_point": datasets.Value("string"),
+                                        "intent": datasets.Value("string"),
+                                        "library": datasets.Sequence(datasets.Value("string")),
+                                        })
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features,
+            supervised_keys=None,
+            citation=_CITATION,
+            homepage=_HOMEPAGE)
+
+    def _split_generators(self, dl_manager):
+        """Returns SplitGenerators."""
+        config_urls = _URLs[self.config.name]
+        data_dir = dl_manager.download_and_extract(config_urls)
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                gen_kwargs={"filepath": data_dir, "split": "train"},
+            ),
+            ]
+
+
+    def _generate_examples(self, filepath, split):
+        key = 0
+        for line in open(filepath, encoding="utf-8"):
+            line = json.loads(line)
+            yield key, line   
+            key += 1