Update CORAA-NURC-SP-Audio-Corpus.py

CORAA-NURC-SP-Audio-Corpus.py

@@ -27,9 +27,20 @@ _PATH_TO_CLIPS = {
 }
 
 
-class NurcSPDataset(datasets.GeneratorBasedBuilder):
+class NurcSPConfig(BuilderConfig):
+    def __init__(self, prompts_type="original", **kwargs):
+        super().__init__(**kwargs)
+        self.prompts_type = prompts_type
+
+
+class NurcSPDataset(GeneratorBasedBuilder):
+    BUILDER_CONFIGS = [
+        NurcSPConfig(name="original", description="Original audio prompts", prompts_type="original"),
+        NurcSPConfig(name="filtered", description="Filtered audio prompts", prompts_type="filtered"),
+    ]
+
     def _info(self):
-        return datasets.DatasetInfo(
+        return DatasetInfo(
             features=datasets.Features(
                 {
                     "audio_name": datasets.Value("string"),
@@ -52,40 +63,34 @@ class NurcSPDataset(datasets.GeneratorBasedBuilder):
             )
         )
 
-    def _split_generators(self, dl_manager, config=None):
-        prompts_urls = _PROMPTS_URLS  # Default to original prompts URLs if config is not provided
-    
-        if config and 'type' in config:
-            prompts_type = config['type']
-            if prompts_type == 'original':
-                prompts_urls = _PROMPTS_URLS
-            elif prompts_type == 'filtered':
-                prompts_urls = _PROMPTS_FILTERED_URLS
-            else:
-                raise ValueError(f"Invalid prompts type '{prompts_type}'. Please choose 'original' or 'filtered'.")
-    
+    def _split_generators(self, dl_manager):
+        prompts_urls = _PROMPTS_URLS  # Default to original prompts URLs
+
+        if self.config.prompts_type == "filtered":
+            prompts_urls = _PROMPTS_FILTERED_URLS
+
         prompts_path = dl_manager.download(prompts_urls)
         archive = dl_manager.download(_ARCHIVES)
-    
+
         return [
-            datasets.SplitGenerator(
-                name=datasets.Split.VALIDATION,
+            SplitGenerator(
+                name=Split.VALIDATION,
                 gen_kwargs={
                     "prompts_path": prompts_path["dev"],
                     "path_to_clips": _PATH_TO_CLIPS["dev"],
                     "audio_files": dl_manager.iter_archive(archive["dev"]),
                 }
             ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TEST,
+            SplitGenerator(
+                name=Split.TEST,
                 gen_kwargs={
                     "prompts_path": prompts_path["test"],
                     "path_to_clips": _PATH_TO_CLIPS["test"],
                     "audio_files": dl_manager.iter_archive(archive["test"]),
                 }
             ),
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
+            SplitGenerator(
+                name=Split.TRAIN,
                 gen_kwargs={
                     "prompts_path": prompts_path["train"],
                     "path_to_clips": _PATH_TO_CLIPS["train"],
@@ -94,7 +99,6 @@ class NurcSPDataset(datasets.GeneratorBasedBuilder):
             ),
         ]
 
-
     def _generate_examples(self, prompts_path, path_to_clips, audio_files):
         examples = {}
         with open(prompts_path, "r") as f:
@@ -142,4 +146,4 @@ class NurcSPDataset(datasets.GeneratorBasedBuilder):
                     yield id_, {**examples[path], "audio": audio}
                     id_ += 1
             elif inside_clips_dir:
-                break
+                break