error fix

snow-mountain.py

@@ -18,7 +18,6 @@ import os
 import csv
 import json
 import datasets
-import zipfile
 import pandas as pd
 from scipy.io import wavfile
 
@@ -95,40 +94,116 @@ class Test(datasets.GeneratorBasedBuilder):
 
     def _split_generators(self, dl_manager):
         
-        downloaded_files = dl_manager.download(_FILES[self.config.name])        
+        downloaded_files = dl_manager.download(_FILES[self.config.name]) 
 
-        data_size = ['500', '1000', '2500', 'short', 'full']
+        train_splits = [
+                datasets.SplitGenerator(
+                    name="train_500",
+                    gen_kwargs={
+                        "filepath": downloaded_files["train_500"],
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name="train_1000",
+                    gen_kwargs={
+                        "filepath": downloaded_files["train_1000"],
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name="train_2500",
+                    gen_kwargs={
+                        "filepath": downloaded_files["train_2500"],
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name="train_short",
+                    gen_kwargs={
+                        "filepath": downloaded_files["train_short"],
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name="train_full",
+                    gen_kwargs={
+                        "filepath": downloaded_files["train_full"],
+                    },
+                ),
+        ]
 
-        splits = []
-        for size in data_size:
-            splits.append(
+        dev_splits = [
                 datasets.SplitGenerator(
-                    name=f"train_{size}",
+                    name="val_500",
                     gen_kwargs={
-                        "filepath": downloaded_files[f"train_{size}"],
-                        "dl_manager": dl_manager,
+                        "filepath": downloaded_files["val_500"],
                     },
-                )
-            )
-            splits.append(
+                ),
                 datasets.SplitGenerator(
-                    name=f"val_{size}",
+                    name="val_1000",
                     gen_kwargs={
-                        "filepath": downloaded_files[f"val_{size}"],
-                        "dl_manager": dl_manager,
+                        "filepath": downloaded_files["val_1000"],
                     },
-                )
-            )
-        splits.append(
-            datasets.SplitGenerator(
-                name="test_common",
-                gen_kwargs={
-                    "filepath": downloaded_files["test_common"],
-                    "dl_manager": dl_manager,
-                },
-            )
-        )
-        return splits
+                ),
+                datasets.SplitGenerator(
+                    name="val_2500",
+                    gen_kwargs={
+                        "filepath": downloaded_files["val_2500"],
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name="val_short",
+                    gen_kwargs={
+                        "filepath": downloaded_files["val_short"],
+                    },
+                ),
+                datasets.SplitGenerator(
+                    name="val_full",
+                    gen_kwargs={
+                        "filepath": downloaded_files["val_full"],
+                    },
+                ),
+        ]
+
+        test_splits = [
+                datasets.SplitGenerator(
+                    name="test_common",
+                    gen_kwargs={
+                        "filepath": downloaded_files["test_common"],
+                    },
+                ),
+        ]
+        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
 
         
     def _generate_examples(self, filepath, dl_manager):