YesNo Dataset Pathlib change (#1015)

Co-authored-by: Vincent QB <vincentqb@users.noreply.github.com>

test/torchaudio_unittest/datasets/yesno_test.py

@@ -1,4 +1,5 @@
 import os
+from pathlib import Path
 
 from torchaudio.datasets import yesno
 
@@ -36,8 +37,7 @@ def setUpClass(cls):
             save_wav(path, data, 8000)
             cls.data.append(normalize_wav(data))
 
-    def test_yesno(self):
-        dataset = yesno.YESNO(self.root_dir)
+    def _test_yesno(self, dataset):
         n_ite = 0
         for i, (waveform, sample_rate, label) in enumerate(dataset):
             expected_label = self.labels[i]
@@ -47,3 +47,11 @@ def test_yesno(self):
             assert label == expected_label
             n_ite += 1
         assert n_ite == len(self.data)
+
+    def test_yesno_str(self):
+        dataset = yesno.YESNO(self.root_dir)
+        self._test_yesno(dataset)
+
+    def test_yesno_path(self):
+        dataset = yesno.YESNO(Path(self.root_dir))
+        self._test_yesno(dataset)

torchaudio/datasets/yesno.py

@@ -1,6 +1,7 @@
 import os
 import warnings
-from typing import Any, List, Tuple
+from typing import Any, List, Tuple, Union
+from pathlib import Path
 
 import torchaudio
 from torch import Tensor
@@ -34,7 +35,7 @@ class YESNO(Dataset):
     """Create a Dataset for YesNo.
 
     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.
             (default: ``"http://www.openslr.org/resources/1/waves_yesno.tar.gz"``)
         folder_in_archive (str, optional):
@@ -48,7 +49,7 @@ class YESNO(Dataset):
     _ext_audio = ".wav"
 
     def __init__(self,
-                 root: str,
+                 root: Union[str, Path],
                  url: str = URL,
                  folder_in_archive: str = FOLDER_IN_ARCHIVE,
                  download: bool = False,
@@ -65,6 +66,9 @@ def __init__(self,
         self.transform = transform
         self.target_transform = target_transform
 
+        # Get string representation of 'root' in case Path object is passed
+        root = os.fspath(root)
+
         archive = os.path.basename(url)
         archive = os.path.join(root, archive)
         self._path = os.path.join(root, folder_in_archive)