error fix

snow-mountain.py

@@ -96,125 +96,38 @@ class Test(datasets.GeneratorBasedBuilder):
         
         downloaded_files = dl_manager.download(_FILES[self.config.name]) 
 
-        train_splits = [
-                datasets.SplitGenerator(
-                    name="train_500",
-                    gen_kwargs={
-                        "filepath": downloaded_files["train_500"],
-                        "dl_manager": dl_manager,
-                    },
-                ),
-                datasets.SplitGenerator(
-                    name="train_1000",
-                    gen_kwargs={
-                        "filepath": downloaded_files["train_1000"],
-                        "dl_manager": dl_manager,
-                    },
-                ),
-                datasets.SplitGenerator(
-                    name="train_2500",
-                    gen_kwargs={
-                        "filepath": downloaded_files["train_2500"],
-                        "dl_manager": dl_manager,
-                    },
-                ),
-                datasets.SplitGenerator(
-                    name="train_short",
-                    gen_kwargs={
-                        "filepath": downloaded_files["train_short"],
-                        "dl_manager": dl_manager,
-                    },
-                ),
-                datasets.SplitGenerator(
-                    name="train_full",
-                    gen_kwargs={
-                        "filepath": downloaded_files["train_full"],
-                        "dl_manager": dl_manager,
-                    },
-                ),
-        ]
+        data_size = ['500', '1000', '2500', 'short', 'full']
 
-        dev_splits = [
-                datasets.SplitGenerator(
-                    name="val_500",
-                    gen_kwargs={
-                        "filepath": downloaded_files["val_500"],
-                        "dl_manager": dl_manager,
-                    },
-                ),
+        splits = []
+        for size in data_size:
+            splits.append(
                 datasets.SplitGenerator(
-                    name="val_1000",
+                    name=f"train_{size}",
                     gen_kwargs={
-                        "filepath": downloaded_files["val_1000"],
+                        "filepath": downloaded_files[f"train_{size}"],
                         "dl_manager": dl_manager,
                     },
-                ),
+                )
+            )
+            splits.append(
                 datasets.SplitGenerator(
-                    name="val_2500",
+                    name=f"val_{size}",
                     gen_kwargs={
-                        "filepath": downloaded_files["val_2500"],
+                        "filepath": downloaded_files[f"val_{size}"],
                         "dl_manager": dl_manager,
                     },
-                ),
-                datasets.SplitGenerator(
-                    name="val_short",
-                    gen_kwargs={
-                        "filepath": downloaded_files["val_short"],
-                        "dl_manager": dl_manager,
-                    },
-                ),
-                datasets.SplitGenerator(
-                    name="val_full",
-                    gen_kwargs={
-                        "filepath": downloaded_files["val_full"],
-                        "dl_manager": dl_manager,
-                    },
-                ),
-        ]
-
-        test_splits = [
-                datasets.SplitGenerator(
-                    name="test_common",
-                    gen_kwargs={
-                        "filepath": downloaded_files["test_common"],
-                        "dl_manager": dl_manager,
-                    },
-                ),
-        ]
-        return train_splits + dev_splits + test_splits       
-
-        # data_size = ['500', '1000', '2500', 'short', 'full']
-
-        # splits = []
-        # for size in data_size:
-        #     splits.append(
-        #         datasets.SplitGenerator(
-        #             name=f"train_{size}",
-        #             gen_kwargs={
-        #                 "filepath": downloaded_files[f"train_{size}"],
-        #                 "dl_manager": dl_manager,
-        #             },
-        #         )
-        #     )
-        #     splits.append(
-        #         datasets.SplitGenerator(
-        #             name=f"val_{size}",
-        #             gen_kwargs={
-        #                 "filepath": downloaded_files[f"val_{size}"],
-        #                 "dl_manager": dl_manager,
-        #             },
-        #         )
-        #     )
-        # splits.append(
-        #     datasets.SplitGenerator(
-        #         name="test_common",
-        #         gen_kwargs={
-        #             "filepath": downloaded_files["test_common"],
-        #             "dl_manager": dl_manager,
-        #         },
-        #     )
-        # )
-        # return splits
+                )
+            )
+        splits.append(
+            datasets.SplitGenerator(
+                name="test_common",
+                gen_kwargs={
+                    "filepath": downloaded_files["test_common"],
+                    "dl_manager": dl_manager,
+                },
+            )
+        )
+        return splits
 
         
     def _generate_examples(self, filepath, dl_manager):