Simplify and remove BuilderConfigs

rixvox.py

@@ -50,18 +50,6 @@ class Rixvox(datasets.GeneratorBasedBuilder):
     VERSION = datasets.Version("1.0.0")
     DEFAULT_CONFIG_NAME = "all"
 
-    BUILDER_CONFIGS = [
-        datasets.BuilderConfig(
-            name="train", version=VERSION, description="Training set of the RixVox dataset. 5383 hours of speech."
-        ),
-        datasets.BuilderConfig(
-            name="dev", version=VERSION, description="Development set of the RixVox dataset. 52 hours of speech."
-        ),
-        datasets.BuilderConfig(
-            name="test", version=VERSION, description="Test set of the RixVox dataset. 59 hours of speech."
-        ),
-    ]
-
     def _info(self):
 
         features = datasets.Features(
@@ -104,20 +92,10 @@ class Rixvox(datasets.GeneratorBasedBuilder):
         splits = ["train", "dev", "test"]
         meta_urls = {split: [_META_URL.format(split=split)] for split in splits}
 
-        if self.config.name == "all":
-            archive_urls = {
-                split: [_DATA_URL.format(split=split, shard_idx=idx) for idx in range(0, _N_SHARDS[split])]
-                for split in splits
-            }
-        else:
-            archive_urls = {
-                self.config.name: [
-                    _DATA_URL.format(split=self.config.name, shard_idx=idx)
-                    for idx in range(0, _N_SHARDS[self.config.name])
-                ]
-            }
-            # Choose single split
-            meta_urls = {self.config.name: meta_urls[self.config.name]}
+        archive_urls = {
+            split: [_DATA_URL.format(split=split, shard_idx=idx) for idx in range(0, _N_SHARDS[split])]
+            for split in splits
+        }
 
         archive_paths = dl_manager.download(archive_urls)
         local_extracted_archives = dl_manager.extract(archive_paths) if not dl_manager.is_streaming else {}
@@ -130,28 +108,14 @@ class Rixvox(datasets.GeneratorBasedBuilder):
             "test": datasets.Split.TEST,
         }
 
-        if self.config.name == "all":
-            for split in splits:
-                split_generators.append(
-                    datasets.SplitGenerator(
-                        name=split_names.get(split),
-                        gen_kwargs={
-                            "local_extracted_archive_paths": local_extracted_archives.get(split),
-                            "archive_iters": [dl_manager.iter_archive(path) for path in archive_paths.get(split)],
-                            "meta_paths": meta_paths[split],
-                        },
-                    ),
-                )
-        else:
+        for split in splits:
             split_generators.append(
                 datasets.SplitGenerator(
-                    name=split_names.get(self.config.name),
+                    name=split_names.get(split),
                     gen_kwargs={
-                        "local_extracted_archive_paths": local_extracted_archives.get(self.config.name),
-                        "archive_iters": [
-                            dl_manager.iter_archive(path) for path in archive_paths.get(self.config.name)
-                        ],
-                        "meta_paths": meta_paths,  # meta_paths is a dict with one key, the split name
+                        "local_extracted_archive_paths": local_extracted_archives.get(split),
+                        "archive_iters": [dl_manager.iter_archive(path) for path in archive_paths.get(split)],
+                        "meta_paths": meta_paths[split],
                     },
                 ),
             )
@@ -167,14 +131,11 @@ class Rixvox(datasets.GeneratorBasedBuilder):
     ):
         key = 0
 
-        if self.config.name == "all":
-            data = []
-            for meta_path in meta_paths.values():
-                data.append(pd.read_parquet(meta_path))
+        data = []
+        for meta_path in meta_paths:
+            data.append(pd.read_parquet(meta_path))
 
-            df_meta = pd.concat(data)
-        else:
-            df_meta = pd.read_parquet(meta_paths[self.config.name])
+        df_meta = pd.concat(data)
 
         df_meta = df_meta.set_index("filename", drop=False)
         # Column contains NAType, so we convert to object type column and NAType to None values.