Add test for Speech Commands dataset (#824)

test/datasets/datasets_test.py

 from torchaudio.datasets.commonvoice import COMMONVOICE
-from torchaudio.datasets.speechcommands import SPEECHCOMMANDS
 from torchaudio.datasets.utils import diskcache_iterator, bg_iterator
 from torchaudio.datasets.vctk import VCTK
 from torchaudio.datasets.cmuarctic import CMUARCTIC
@@ -18,10 +17,6 @@ class TestDatasets(TorchaudioTestCase):
         data = VCTK(self.path)
         data[0]
 
-    def test_speechcommands(self):
-        data = SPEECHCOMMANDS(self.path)
-        data[0]
-
     def test_cmuarctic(self):
         data = CMUARCTIC(self.path)
         data[0]

test/datasets/speechcommands_test.py

+import os
+
+from torchaudio.datasets import speechcommands
+
+from ..common_utils import (
+    TempDirMixin,
+    TorchaudioTestCase,
+    get_whitenoise,
+    normalize_wav,
+    save_wav,
+)
+
+LABELS = [
+    "bed",
+    "bird",
+    "cat",
+    "dog",
+    "down",
+    "eight",
+    "five",
+    "follow",
+    "forward",
+    "four",
+    "go",
+    "happy",
+    "house",
+    "learn",
+    "left",
+    "marvin",
+    "nine",
+    "no",
+    "off",
+    "on",
+    "one",
+    "right",
+    "seven",
+    "sheila",
+    "six",
+    "stop",
+    "three",
+    "tree",
+    "two",
+    "up",
+    "visual",
+    "wow",
+    "yes",
+    "zero",
+]
+
+
+class TestSpeechCommands(TempDirMixin, TorchaudioTestCase):
+    backend = "default"
+
+    root_dir = None
+    samples = []
+
+    @classmethod
+    def setUp(cls):
+        cls.root_dir = cls.get_base_temp_dir()
+        dataset_dir = os.path.join(
+            cls.root_dir, speechcommands.FOLDER_IN_ARCHIVE, speechcommands.URL
+        )
+        os.makedirs(dataset_dir, exist_ok=True)
+        sample_rate = 16000  # 16kHz sample rate
+        seed = 0
+        for label in LABELS:
+            path = os.path.join(dataset_dir, label)
+            os.makedirs(path, exist_ok=True)
+            for j in range(2):
+                # generate hash ID for speaker
+                speaker = "{:08x}".format(j)
+
+                for utterance in range(3):
+                    filename = f"{speaker}{speechcommands.HASH_DIVIDER}{utterance}.wav"
+                    file_path = os.path.join(path, filename)
+                    seed += 1
+                    data = get_whitenoise(
+                        sample_rate=sample_rate,
+                        duration=0.01,
+                        n_channels=1,
+                        dtype="int16",
+                        seed=seed,
+                    )
+                    save_wav(file_path, data, sample_rate)
+                    sample = (
+                        normalize_wav(data),
+                        sample_rate,
+                        label,
+                        speaker,
+                        utterance,
+                    )
+                    cls.samples.append(sample)
+
+    def testSpeechCommands(self):
+        dataset = speechcommands.SPEECHCOMMANDS(self.root_dir)
+        print(dataset._path)
+
+        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
+
+        assert num_samples == len(self.samples)