Update test_repo.py

test_repo.py

@@ -42,9 +42,8 @@ class TestRepo(datasets.GeneratorBasedBuilder):
 #     DEFAULT_CONFIG_NAME = "mcq_domain"
 
     def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features({
+        features_dict = {
+            "train_normal_mcqa": datasets.Features({
                 "prompt": datasets.Value("string"),
                 "question": datasets.Value("string"),
                 "options": datasets.Sequence(datasets.Value("string")),
@@ -53,6 +52,39 @@ class TestRepo(datasets.GeneratorBasedBuilder):
                 "question_type": datasets.Value("string"),
                 "dataset_name": datasets.Value("string"),
             }),
+            "val_normal_mcqa": datasets.Features({
+                "prompt": datasets.Value("string"),
+                "question": datasets.Value("string"),
+                "options": datasets.Sequence(datasets.Value("string")),
+                "answer": datasets.Value("string"),
+                "num_options": datasets.Value("string"),
+                "question_type": datasets.Value("string"),
+                "dataset_name": datasets.Value("string"),
+                "few_shot_prompt": datasets.Sequence(datasets.Features({
+                    "question": datasets.Value("string"),
+                    "answer": datasets.Value("string"),
+                    "options": datasets.Sequence(datasets.Value("string")),
+                })),                
+            }),
+            "test_normal_mcqa": datasets.Features({
+                "prompt": datasets.Value("string"),
+                "question": datasets.Value("string"),
+                "options": datasets.Sequence(datasets.Value("string")),
+                "answer": datasets.Value("string"),
+                "num_options": datasets.Value("string"),
+                "question_type": datasets.Value("string"),
+                "dataset_name": datasets.Value("string"),
+                "few_shot_prompt": datasets.Sequence(datasets.Features({
+                    "question": datasets.Value("string"),
+                    "answer": datasets.Value("string"),
+                    "options": datasets.Sequence(datasets.Value("string")),
+                })),                
+            })            
+        }
+        
+        return datasets.DatasetInfo(
+            description=_DESCRIPTION,
+            features=features_dict[self.config.name]
             homepage=_HOMEPAGE,
             license=_LICENSE,
             citation=_CITATION,
@@ -64,9 +96,17 @@ class TestRepo(datasets.GeneratorBasedBuilder):
         print(data_dir)
         return [
             datasets.SplitGenerator(
-                name=self.config.name,
-                gen_kwargs={"directory": data_dir, "split": self.config.name},
-            )
+                name="train_normal_mcqa",
+                gen_kwargs={"directory": data_dir, "split": "train"},
+            ),
+            datasets.SplitGenerator(
+                name="val_normal_mcqa",
+                gen_kwargs={"directory": data_dir, "split": "val"},
+            ),
+            datasets.SplitGenerator(
+                name="test_normal_mcqa",
+                gen_kwargs={"directory": data_dir, "split": "test"},
+            ),            
         ]
 
     def _generate_examples(self, directory, split):
@@ -78,7 +118,7 @@ class TestRepo(datasets.GeneratorBasedBuilder):
                 with open(filepath, encoding="utf-8") as f:
                     for key, row in enumerate(f):
                         data = json.loads(row)
-                        if split in ["train_normal_mcqa", "val_normal_mcqa", "test_normal_mcqa"]:
+                        if split == "train_normal_mcqa":
                             yield key_idx, {
                                 "prompt": data.get("prompt", ""),
                                 "question": data["question"],
@@ -88,4 +128,21 @@ class TestRepo(datasets.GeneratorBasedBuilder):
                                 "question_type": data.get("question_type", ""),
                                 "dataset_name": os.path.split(filepath)[-1].replace(".jsonl","")
                             }
+                            key_idx +=1
+                        elif split in ["val_normal_mcqa", "test_normal_mcqa"]:
+                            yield key_idx, {
+                                "prompt": data.get("prompt", ""),
+                                "question": data["question"],
+                                "options": data["options"],
+                                "answer": data.get("answer", ""),
+                                "num_options": data.get("num_options", ""),
+                                "question_type": data.get("question_type", ""),
+                                "dataset_name": os.path.split(filepath)[-1].replace(".jsonl",""),
+                                "few_shot_prompt": [{
+                                "question": item["question"],
+                                "answer": item["answer"],
+                                "options": item["options"],
+                            } for item in data["few_shot_prompt"]]
+                            }
+                                                        
                             key_idx +=1