Update librispeech_test_only.py

librispeech_test_only.py

@@ -46,24 +46,14 @@ _DL_URL = "http://www.openslr.org/resources/12/"
 
 _DL_URLS = {
     "clean": {
-        "dev": _DL_URL + "dev-clean.tar.gz",
-        "test": _DL_URL + "test-clean.tar.gz",
-#        "train.100": _DL_URL + "train-clean-100.tar.gz",
-#        "train.360": _DL_URL + "train-clean-360.tar.gz",
+        "test": _DL_URL + "test-clean.tar.gz"
     },
     "other": {
-        "test": _DL_URL + "test-other.tar.gz",
-        "dev": _DL_URL + "dev-other.tar.gz",
-#        "train.500": _DL_URL + "train-other-500.tar.gz",
+        "test": _DL_URL + "test-other.tar.gz"
     },
     "all": {
-        "dev.clean": _DL_URL + "dev-clean.tar.gz",
-        "dev.other": _DL_URL + "dev-other.tar.gz",
         "test.clean": _DL_URL + "test-clean.tar.gz",
-        "test.other": _DL_URL + "test-other.tar.gz",
-#        "train.clean.100": _DL_URL + "train-clean-100.tar.gz",
-#        "train.clean.360": _DL_URL + "train-clean-360.tar.gz",
-#        "train.other.500": _DL_URL + "train-other-500.tar.gz",
+        "test.other": _DL_URL + "test-other.tar.gz"
     },
 }
 
@@ -117,38 +107,8 @@ class LibrispeechASR(datasets.GeneratorBasedBuilder):
         archive_path = dl_manager.download(_DL_URLS[self.config.name])
         # (Optional) In non-streaming mode, we can extract the archive locally to have actual local audio files:
         local_extracted_archive = dl_manager.extract(archive_path) if not dl_manager.is_streaming else {}
-        
-        train_splits = list()
-        dev_splits = list()
 
         if self.config.name == "clean":
-            """
-            train_splits = [
-                datasets.SplitGenerator(
-                    name="train.100",
-                    gen_kwargs={
-                        "local_extracted_archive": local_extracted_archive.get("train.100"),
-                        "files": dl_manager.iter_archive(archive_path["train.100"]),
-                    },
-                ),
-                datasets.SplitGenerator(
-                    name="train.360",
-                    gen_kwargs={
-                        "local_extracted_archive": local_extracted_archive.get("train.360"),
-                        "files": dl_manager.iter_archive(archive_path["train.360"]),
-                    },
-                ),
-            ]
-            dev_splits = [
-                datasets.SplitGenerator(
-                    name=datasets.Split.VALIDATION,
-                    gen_kwargs={
-                        "local_extracted_archive": local_extracted_archive.get("dev"),
-                        "files": dl_manager.iter_archive(archive_path["dev"]),
-                    },
-                )
-            ]
-            """
             test_splits = [
                 datasets.SplitGenerator(
                     name=datasets.Split.TEST,
@@ -159,26 +119,6 @@ class LibrispeechASR(datasets.GeneratorBasedBuilder):
                 )
             ]
         elif self.config.name == "other":
-            """
-            train_splits = [
-                datasets.SplitGenerator(
-                    name="train.500",
-                    gen_kwargs={
-                        "local_extracted_archive": local_extracted_archive.get("train.500"),
-                        "files": dl_manager.iter_archive(archive_path["train.500"]),
-                    },
-                )
-            ]
-            dev_splits = [
-                datasets.SplitGenerator(
-                    name=datasets.Split.VALIDATION,
-                    gen_kwargs={
-                        "local_extracted_archive": local_extracted_archive.get("dev"),
-                        "files": dl_manager.iter_archive(archive_path["dev"]),
-                    },
-                )
-            ]
-            """
             test_splits = [
                 datasets.SplitGenerator(
                     name=datasets.Split.TEST,
@@ -189,47 +129,6 @@ class LibrispeechASR(datasets.GeneratorBasedBuilder):
                 )
             ]
         elif self.config.name == "all":
-            """
-            train_splits = [
-                datasets.SplitGenerator(
-                    name="train.clean.100",
-                    gen_kwargs={
-                        "local_extracted_archive": local_extracted_archive.get("train.clean.100"),
-                        "files": dl_manager.iter_archive(archive_path["train.clean.100"]),
-                    },
-                ),
-                datasets.SplitGenerator(
-                    name="train.clean.360",
-                    gen_kwargs={
-                        "local_extracted_archive": local_extracted_archive.get("train.clean.360"),
-                        "files": dl_manager.iter_archive(archive_path["train.clean.360"]),
-                    },
-                ),
-                datasets.SplitGenerator(
-                    name="train.other.500",
-                    gen_kwargs={
-                        "local_extracted_archive": local_extracted_archive.get("train.other.500"),
-                        "files": dl_manager.iter_archive(archive_path["train.other.500"]),
-                    },
-                ),
-            ]
-            dev_splits = [
-                datasets.SplitGenerator(
-                    name="validation.clean",
-                    gen_kwargs={
-                        "local_extracted_archive": local_extracted_archive.get("validation.clean"),
-                        "files": dl_manager.iter_archive(archive_path["dev.clean"]),
-                    },
-                ),
-                datasets.SplitGenerator(
-                    name="validation.other",
-                    gen_kwargs={
-                        "local_extracted_archive": local_extracted_archive.get("validation.other"),
-                        "files": dl_manager.iter_archive(archive_path["dev.other"]),
-                    },
-                ),
-            ]
-            """
             test_splits = [
                 datasets.SplitGenerator(
                     name="test.clean",
@@ -247,7 +146,7 @@ class LibrispeechASR(datasets.GeneratorBasedBuilder):
                 ),
             ]
 
-        return train_splits + dev_splits + test_splits
+        return test_splits
 
     def _generate_examples(self, files, local_extracted_archive):
         """Generate examples from a LibriSpeech archive_path."""