Add pathlib support for LIBRITTS and LIBRISPEECH (#1046)

test/torchaudio_unittest/datasets/librispeech_test.py

 import os
+from pathlib import Path
 
 from torchaudio.datasets import librispeech
 
@@ -91,11 +92,7 @@ class TestLibriSpeech(TempDirMixin, TorchaudioTestCase):
         # In case of test failure
         librispeech.LIBRISPEECH._ext_audio = '.flac'
 
-    def test_librispeech(self):
-        librispeech.LIBRISPEECH._ext_audio = '.wav'
-        dataset = librispeech.LIBRISPEECH(self.root_dir)
-        print(dataset._path)
-
+    def _test_librispeech(self, dataset):
         num_samples = 0
         for i, (
             data, sample_rate, utterance, speaker_id, chapter_id, utterance_id
@@ -110,3 +107,13 @@ class TestLibriSpeech(TempDirMixin, TorchaudioTestCase):
 
         assert num_samples == len(self.samples)
         librispeech.LIBRISPEECH._ext_audio = '.flac'
+
+    def test_librispeech_str(self):
+        librispeech.LIBRISPEECH._ext_audio = '.wav'
+        dataset = librispeech.LIBRISPEECH(self.root_dir)
+        self._test_librispeech(dataset)
+
+    def test_librispeech_path(self):
+        librispeech.LIBRISPEECH._ext_audio = '.wav'
+        dataset = librispeech.LIBRISPEECH(Path(self.root_dir))
+        self._test_librispeech(dataset)

test/torchaudio_unittest/datasets/libritts_test.py

 import os
+from pathlib import Path
 
 from torchaudio.datasets.libritts import LIBRITTS
 
@@ -47,8 +48,7 @@ class TestLibriTTS(TempDirMixin, TorchaudioTestCase):
             with open(path_normalized, 'w') as file_:
                 file_.write(cls.normalized_text)
 
-    def test_libritts(self):
-        dataset = LIBRITTS(self.root_dir)
+    def _test_libritts(self, dataset):
         n_ites = 0
         for i, (waveform,
                 sample_rate,
@@ -69,3 +69,11 @@ class TestLibriTTS(TempDirMixin, TorchaudioTestCase):
             assert utterance_id == f'{"_".join(str(u) for u in expected_ids[-4:])}'
             n_ites += 1
         assert n_ites == len(self.utterance_ids)
+
+    def test_libritts_str(self):
+        dataset = LIBRITTS(self.root_dir)
+        self._test_libritts(dataset)
+
+    def test_libritts_path(self):
+        dataset = LIBRITTS(Path(self.root_dir))
+        self._test_libritts(dataset)

torchaudio/datasets/librispeech.py

 import os
-from typing import Tuple
+from typing import Tuple, Union
+from pathlib import Path
 
 import torchaudio
 from torch import Tensor
@@ -70,7 +71,7 @@ class LIBRISPEECH(Dataset):
     """Create a Dataset for LibriSpeech.
 
     Args:
-        root (str): Path to the directory where the dataset is found or downloaded.
+        root (str or Path): Path to the directory where the dataset is found or downloaded.
         url (str, optional): The URL to download the dataset from,
             or the type of the dataset to dowload.
             Allowed type values are ``"dev-clean"``, ``"dev-other"``, ``"test-clean"``,
@@ -86,7 +87,7 @@ class LIBRISPEECH(Dataset):
     _ext_audio = ".flac"
 
     def __init__(self,
-                 root: str,
+                 root: Union[str, Path],
                  url: str = URL,
                  folder_in_archive: str = FOLDER_IN_ARCHIVE,
                  download: bool = False) -> None:
@@ -106,6 +107,9 @@ class LIBRISPEECH(Dataset):
 
             url = os.path.join(base_url, url + ext_archive)
 
+        # Get string representation of 'root' in case Path object is passed
+        root = os.fspath(root)
+
         basename = os.path.basename(url)
         archive = os.path.join(root, basename)
 

torchaudio/datasets/libritts.py

 import os
-from typing import Tuple
+from typing import Tuple, Union
+from pathlib import Path
 
 import torchaudio
 from torch import Tensor
@@ -68,7 +69,7 @@ class LIBRITTS(Dataset):
     """Create a Dataset for LibriTTS.
 
     Args:
-        root (str): Path to the directory where the dataset is found or downloaded.
+        root (str or Path): Path to the directory where the dataset is found or downloaded.
         url (str, optional): The URL to download the dataset from,
             or the type of the dataset to dowload.
             Allowed type values are ``"dev-clean"``, ``"dev-other"``, ``"test-clean"``,
@@ -86,7 +87,7 @@ class LIBRITTS(Dataset):
 
     def __init__(
         self,
-        root: str,
+        root: Union[str, Path],
         url: str = URL,
         folder_in_archive: str = FOLDER_IN_ARCHIVE,
         download: bool = False,
@@ -107,6 +108,9 @@ class LIBRITTS(Dataset):
 
             url = os.path.join(base_url, url + ext_archive)
 
+        # Get string representation of 'root' in case Path object is passed
+        root = os.fspath(root)
+
         basename = os.path.basename(url)
         archive = os.path.join(root, basename)