train_test_split

dusha_emotion_audio.py

@@ -11,8 +11,10 @@ The corpus contains approximately 350 hours of data. Four basic emotions that us
 
 _HOMEPAGE = "https://github.com/salute-developers/golos/tree/master/dusha#dusha-dataset"
 
-_DATA_URL = "https://huggingface.co/datasets/KELONMYOSA/dusha_emotion_audio/resolve/main/data/data.tar.gz"
-_METADATA_URL = "https://huggingface.co/datasets/KELONMYOSA/dusha_emotion_audio/resolve/main/data/labels.csv"
+_DATA_URL_TRAIN = "https://huggingface.co/datasets/KELONMYOSA/dusha_emotion_audio/resolve/main/data/train.tar.gz"
+_DATA_URL_TEST = "https://huggingface.co/datasets/KELONMYOSA/dusha_emotion_audio/resolve/main/data/test.tar.gz"
+_METADATA_URL_TRAIN = "https://huggingface.co/datasets/KELONMYOSA/dusha_emotion_audio/resolve/main/data/train.csv"
+_METADATA_URL_TEST = "https://huggingface.co/datasets/KELONMYOSA/dusha_emotion_audio/resolve/main/data/test.csv"
 
 
 class Dusha(datasets.GeneratorBasedBuilder):
@@ -33,14 +35,24 @@ class Dusha(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        metadata = dl_manager.download(_METADATA_URL)
-        archive = dl_manager.download(_DATA_URL)
-        return [datasets.SplitGenerator(
+        metadata_train = dl_manager.download(_METADATA_URL_TRAIN)
+        metadata_test = dl_manager.download(_METADATA_URL_TEST)
+        archive_train = dl_manager.download(_DATA_URL_TRAIN)
+        archive_test = dl_manager.download(_DATA_URL_TEST)
+        return [
+        datasets.SplitGenerator(
             name=datasets.Split.TRAIN,
             gen_kwargs={
-                "audio_files": dl_manager.iter_archive(archive),
-                "metadata": metadata},
-        )]
+                "audio_files": dl_manager.iter_archive(archive_train),
+                "metadata": metadata_train},
+        ),
+        datasets.SplitGenerator(
+            name=datasets.Split.TEST,
+            gen_kwargs={
+                "audio_files": dl_manager.iter_archive(archive_test),
+                "metadata": metadata_test},
+        )
+        ]
 
     def _generate_examples(self, audio_files, metadata):
         examples = dict()