Add pathlib support for SPEECHCOMMANDS (#1039)

test/torchaudio_unittest/datasets/speechcommands_test.py

 import os
+from pathlib import Path
 
 from torchaudio.datasets import speechcommands
 
@@ -105,85 +106,39 @@ class TestSpeechCommands(TempDirMixin, TorchaudioTestCase):
                             test.write(f'{label}/{filename}\n')
                             cls.test_samples.append(sample)
 
-    def testSpeechCommands(self):
-        dataset = speechcommands.SPEECHCOMMANDS(self.root_dir)
-
+    def _testSpeechCommands(self, dataset, data_samples):
         num_samples = 0
         for i, (data, sample_rate, label, speaker_id, utterance_number) in enumerate(
             dataset
         ):
-            self.assertEqual(data, self.samples[i][0], atol=5e-5, rtol=1e-8)
-            assert sample_rate == self.samples[i][1]
-            assert label == self.samples[i][2]
-            assert speaker_id == self.samples[i][3]
-            assert utterance_number == self.samples[i][4]
+            self.assertEqual(data, data_samples[i][0], atol=5e-5, rtol=1e-8)
+            assert sample_rate == data_samples[i][1]
+            assert label == data_samples[i][2]
+            assert speaker_id == data_samples[i][3]
+            assert utterance_number == data_samples[i][4]
             num_samples += 1
 
-        assert num_samples == len(self.samples)
+        assert num_samples == len(data_samples)
 
-    def testSpeechCommandsNone(self):
-        dataset = speechcommands.SPEECHCOMMANDS(self.root_dir, subset=None)
-
-        num_samples = 0
-        for i, (data, sample_rate, label, speaker_id, utterance_number) in enumerate(
-            dataset
-        ):
-            self.assertEqual(data, self.samples[i][0], atol=5e-5, rtol=1e-8)
-            assert sample_rate == self.samples[i][1]
-            assert label == self.samples[i][2]
-            assert speaker_id == self.samples[i][3]
-            assert utterance_number == self.samples[i][4]
-            num_samples += 1
+    def testSpeechCommands_str(self):
+        dataset = speechcommands.SPEECHCOMMANDS(self.root_dir)
+        self._testSpeechCommands(dataset, self.samples)
 
-        assert num_samples == len(self.samples)
+    def testSpeechCommands_path(self):
+        dataset = speechcommands.SPEECHCOMMANDS(Path(self.root_dir))
+        self._testSpeechCommands(dataset, self.samples)
 
     def testSpeechCommandsSubsetTrain(self):
         dataset = speechcommands.SPEECHCOMMANDS(self.root_dir, subset="training")
-
-        num_samples = 0
-        for i, (data, sample_rate, label, speaker_id, utterance_number) in enumerate(
-            dataset
-        ):
-            self.assertEqual(data, self.train_samples[i][0], atol=5e-5, rtol=1e-8)
-            assert sample_rate == self.train_samples[i][1]
-            assert label == self.train_samples[i][2]
-            assert speaker_id == self.train_samples[i][3]
-            assert utterance_number == self.train_samples[i][4]
-            num_samples += 1
-
-        assert num_samples == len(self.train_samples)
+        self._testSpeechCommands(dataset, self.train_samples)
 
     def testSpeechCommandsSubsetValid(self):
         dataset = speechcommands.SPEECHCOMMANDS(self.root_dir, subset="validation")
-
-        num_samples = 0
-        for i, (data, sample_rate, label, speaker_id, utterance_number) in enumerate(
-            dataset
-        ):
-            self.assertEqual(data, self.valid_samples[i][0], atol=5e-5, rtol=1e-8)
-            assert sample_rate == self.valid_samples[i][1]
-            assert label == self.valid_samples[i][2]
-            assert speaker_id == self.valid_samples[i][3]
-            assert utterance_number == self.valid_samples[i][4]
-            num_samples += 1
-
-        assert num_samples == len(self.valid_samples)
+        self._testSpeechCommands(dataset, self.valid_samples)
 
     def testSpeechCommandsSubsetTest(self):
         dataset = speechcommands.SPEECHCOMMANDS(self.root_dir, subset="testing")
-
-        num_samples = 0
-        for i, (data, sample_rate, label, speaker_id, utterance_number) in enumerate(
-            dataset
-        ):
-            self.assertEqual(data, self.test_samples[i][0], atol=5e-5, rtol=1e-8)
-            assert sample_rate == self.test_samples[i][1]
-            assert label == self.test_samples[i][2]
-            assert speaker_id == self.test_samples[i][3]
-            assert utterance_number == self.test_samples[i][4]
-            num_samples += 1
-
-        assert num_samples == len(self.test_samples)
+        self._testSpeechCommands(dataset, self.test_samples)
 
     def testSpeechCommandsSum(self):
         dataset_all = speechcommands.SPEECHCOMMANDS(self.root_dir)

torchaudio/datasets/speechcommands.py

 import os
-from typing import Tuple, Optional
+from typing import Tuple, Optional, Union
+from pathlib import Path
 
 import torchaudio
 from torch.utils.data import Dataset
@@ -48,7 +49,7 @@ class SPEECHCOMMANDS(Dataset):
     """Create a Dataset for Speech Commands.
 
     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 ``"speech_commands_v0.01"`` and ``"speech_commands_v0.02"``
@@ -64,7 +65,7 @@ class SPEECHCOMMANDS(Dataset):
     """
 
     def __init__(self,
-                 root: str,
+                 root: Union[str, Path],
                  url: str = URL,
                  folder_in_archive: str = FOLDER_IN_ARCHIVE,
                  download: bool = False,
@@ -85,6 +86,9 @@ class SPEECHCOMMANDS(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)