Update semi-homo.py

semi-homo.py

@@ -1,6 +1,7 @@
 import os
 import datasets
 import pandas as pd
+import json
 
 
 class semiHomoConfig(datasets.BuilderConfig):
@@ -19,7 +20,22 @@ class semiHomo(datasets.GeneratorBasedBuilder):
                 "rtable_id": datasets.Value("string"),
                 "label": datasets.Value("string"),
             },
-            data_url="https://huggingface.co/datasets/matchbench/semi-Homo/resolve/main/",
+            data_url="https://huggingface.co/datasets/matchbench/semi-homo/resolve/main/",
+        ),
+        semiHomoConfig(
+            name="source",
+            features={
+                "content": datasets.Value("string"),
+            },
+            data_url="https://huggingface.co/datasets/matchbench/semi-homo/resolve/main/left.json",
+        ),
+
+        semihomoConfig(
+            name="target",
+            features={
+                "content": datasets.Value("string"),
+            },
+            data_url="https://huggingface.co/datasets/matchbench/semi-homo/resolve/main/right.json",
         ),
     ]
 
@@ -42,13 +58,27 @@ class semiHomo(datasets.GeneratorBasedBuilder):
                 for split in ["train", "valid", "test"]
             ]
 
+        if self.config.name == "source":
+            return [datasets.SplitGenerator(name="source", gen_kwargs={
+                "path_file": dl_manager.download_and_extract(self.config.data_url), "split": "source", })]
+
+        if self.config.name == "target":
+            return [datasets.SplitGenerator(name="target", gen_kwargs={
+                "path_file": dl_manager.download_and_extract(self.config.data_url), "split": "target", })]
+
     def _generate_examples(self, path_file, split):
-        file = pd.read_csv(path_file)
-        for i, row in file.iterrows():
-            if split  in ['train', 'valid','test']:
+        if split in ['source','target']:
+            with open(path_file, "r") as f:
+                file = json.load(f)
+            for i in range(len(file)):
                 yield i, {
-                    "ltable_id": row["ltable_id"],
-                    "rtable_id": row["rtable_id"],
-                    "label": row["label"],
+                    "content": file[i]
                 }
-
+        else:
+            file = pd.read_csv(path_file)
+            for i, row in file.iterrows():
+                    yield i, {
+                        "ltable_id": row["ltable_id"],
+                        "rtable_id": row["rtable_id"],
+                        "label": row["label"],
+                    }