Add pathlib.Path support to `gtzan` (#1032)

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

test/torchaudio_unittest/datasets/gtzan_test.py

 import os
+from pathlib import Path
 
 from torchaudio.datasets import gtzan
 
@@ -54,9 +55,7 @@ class TestGTZAN(TempDirMixin, TorchaudioTestCase):
             n_ite += 1
         assert n_ite == len(self.samples)
 
-    def test_training(self):
-        dataset = gtzan.GTZAN(self.root_dir, subset='training')
-
+    def _test_training(self, dataset):
         n_ite = 0
         for i, (waveform, sample_rate, label) in enumerate(dataset):
             self.assertEqual(waveform, self.training[i][0], atol=5e-5, rtol=1e-8)
@@ -65,9 +64,7 @@ class TestGTZAN(TempDirMixin, TorchaudioTestCase):
             n_ite += 1
         assert n_ite == len(self.training)
 
-    def test_validation(self):
-        dataset = gtzan.GTZAN(self.root_dir, subset='validation')
-
+    def _test_validation(self, dataset):
         n_ite = 0
         for i, (waveform, sample_rate, label) in enumerate(dataset):
             self.assertEqual(waveform, self.validation[i][0], atol=5e-5, rtol=1e-8)
@@ -76,9 +73,7 @@ class TestGTZAN(TempDirMixin, TorchaudioTestCase):
             n_ite += 1
         assert n_ite == len(self.validation)
 
-    def test_testing(self):
-        dataset = gtzan.GTZAN(self.root_dir, subset='testing')
-
+    def _test_testing(self, dataset):
         n_ite = 0
         for i, (waveform, sample_rate, label) in enumerate(dataset):
             self.assertEqual(waveform, self.testing[i][0], atol=5e-5, rtol=1e-8)
@@ -86,3 +81,30 @@ class TestGTZAN(TempDirMixin, TorchaudioTestCase):
             assert label == self.testing[i][2]
             n_ite += 1
         assert n_ite == len(self.testing)
+
+    def test_training_str(self):
+        train_dataset = gtzan.GTZAN(self.root_dir, subset='training')
+        self._test_training(train_dataset)
+
+    def test_validation_str(self):
+        val_dataset = gtzan.GTZAN(self.root_dir, subset='validation')
+        self._test_validation(val_dataset)
+
+    def test_testing_str(self):
+        test_dataset = gtzan.GTZAN(self.root_dir, subset='testing')
+        self._test_testing(test_dataset)
+
+    def test_training_path(self):
+        root_dir = Path(self.root_dir)
+        train_dataset = gtzan.GTZAN(root_dir, subset='training')
+        self._test_training(train_dataset)
+
+    def test_validation_path(self):
+        root_dir = Path(self.root_dir)
+        val_dataset = gtzan.GTZAN(root_dir, subset='validation')
+        self._test_validation(val_dataset)
+
+    def test_testing_path(self):
+        root_dir = Path(self.root_dir)
+        test_dataset = gtzan.GTZAN(root_dir, subset='testing')
+        self._test_testing(test_dataset)

torchaudio/datasets/gtzan.py

 import os
 import warnings
-from typing import Any, Tuple, Optional
+from pathlib import Path
+from typing import Any, Tuple, Optional, Union
 
 import torchaudio
 from torch import Tensor
@@ -1005,7 +1006,7 @@ class GTZAN(Dataset):
         this dataset to publish results.
 
     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://opihi.cs.uvic.ca/sound/genres.tar.gz"``)
         folder_in_archive (str, optional): The top-level directory of the dataset.
@@ -1020,7 +1021,7 @@ class GTZAN(Dataset):
 
     def __init__(
         self,
-        root: str,
+        root: Union[str, Path],
         url: str = URL,
         folder_in_archive: str = FOLDER_IN_ARCHIVE,
         download: bool = False,
@@ -1028,6 +1029,10 @@ class GTZAN(Dataset):
     ) -> None:
 
         # super(GTZAN, self).__init__()
+
+        # Get string representation of 'root' in case Path object is passed
+        root = os.fspath(root)
+
         self.root = root
         self.url = url
         self.folder_in_archive = folder_in_archive