Make Dataset utility test independent of CommonVoice (#1132)

test/torchaudio_unittest/assets/CommonVoice/cv-corpus-4-2019-12-10/tt/train.tsv

-client_id	path	sentence	up_votes	down_votes	age	gender	accent
-00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000	common_voice_tt_00000000.wav	test.	1	0	thirties	female	
-00000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001	common_voice_tt_00000000.wav	test.	1	0	thirties	female	

test/torchaudio_unittest/datasets/utils_test.py

+import torch
 from torchaudio_unittest.common_utils import (
     TorchaudioTestCase,
-    get_asset_path,
+    TempDirMixin
 )
 
 from torchaudio.datasets import utils as dataset_utils
-from torchaudio.datasets.commonvoice import COMMONVOICE
 
-original_ext_audio = COMMONVOICE._ext_audio
 
+class Dataset(torch.utils.data.Dataset):
+    def __getitem__(self, n):
+        sample_rate = 8000
+        waveform = n * torch.ones(2, 256)
+        return waveform, sample_rate
 
-class TestIterator(TorchaudioTestCase):
-    @classmethod
-    def setUpClass(cls):
-        COMMONVOICE._ext_audio = ".wav"
+    def __len__(self) -> int:
+        return 2
 
-    @classmethod
-    def tearDownClass(cls):
-        COMMONVOICE._ext_audio = original_ext_audio
+    def __iter__(self):
+        for i in range(len(self)):
+            yield self[i]
 
+
+class TestIterator(TorchaudioTestCase, TempDirMixin):
     backend = 'default'
-    path = get_asset_path('CommonVoice', 'cv-corpus-4-2019-12-10', 'tt')
 
     def test_disckcache_iterator(self):
-        data = COMMONVOICE(self.path, url="tatar")
-        data = dataset_utils.diskcache_iterator(data)
+        data = dataset_utils.diskcache_iterator(Dataset(), self.get_base_temp_dir())
         # Save
         data[0]
         # Load
         data[0]
 
     def test_bg_iterator(self):
-        data = COMMONVOICE(self.path, url="tatar")
-        data = dataset_utils.bg_iterator(data, 5)
+        data = dataset_utils.bg_iterator(Dataset(), 5)
         for _ in data:
             pass