Refactor GTZAN unittest (#1148)

Co-authored-by: krishnakalyan3 <skalyan@cloudera.com>

test/torchaudio_unittest/datasets/gtzan_test.py

@@ -12,6 +12,37 @@ from torchaudio_unittest.common_utils import (
 )
 
 
+def get_mock_dataset(root_dir):
+    """
+    root_dir: directory to the mocked dataset
+    """
+    mocked_samples = []
+    mocked_training = []
+    mocked_validation = []
+    mocked_testing = []
+    sample_rate = 22050
+
+    seed = 0
+    for genre in gtzan.gtzan_genres:
+        base_dir = os.path.join(root_dir, 'genres', genre)
+        os.makedirs(base_dir, exist_ok=True)
+        for i in range(100):
+            filename = f'{genre}.{i:05d}'
+            path = os.path.join(base_dir, f'{filename}.wav')
+            data = get_whitenoise(sample_rate=sample_rate, duration=0.01, n_channels=1, dtype='int16', seed=seed)
+            save_wav(path, data, sample_rate)
+            sample = (normalize_wav(data), sample_rate, genre)
+            mocked_samples.append(sample)
+            if filename in gtzan.filtered_test:
+                mocked_testing.append(sample)
+            if filename in gtzan.filtered_train:
+                mocked_training.append(sample)
+            if filename in gtzan.filtered_valid:
+                mocked_validation.append(sample)
+            seed += 1
+    return (mocked_samples, mocked_training, mocked_validation, mocked_testing)
+
+
 class TestGTZAN(TempDirMixin, TorchaudioTestCase):
     backend = 'default'
 
@@ -24,25 +55,11 @@ class TestGTZAN(TempDirMixin, TorchaudioTestCase):
     @classmethod
     def setUpClass(cls):
         cls.root_dir = cls.get_base_temp_dir()
-        sample_rate = 22050
-        seed = 0
-        for genre in gtzan.gtzan_genres:
-            base_dir = os.path.join(cls.root_dir, 'genres', genre)
-            os.makedirs(base_dir, exist_ok=True)
-            for i in range(100):
-                filename = f'{genre}.{i:05d}'
-                path = os.path.join(base_dir, f'{filename}.wav')
-                data = get_whitenoise(sample_rate=sample_rate, duration=0.01, n_channels=1, dtype='int16', seed=seed)
-                save_wav(path, data, sample_rate)
-                sample = (normalize_wav(data), sample_rate, genre)
-                cls.samples.append(sample)
-                if filename in gtzan.filtered_test:
-                    cls.testing.append(sample)
-                if filename in gtzan.filtered_train:
-                    cls.training.append(sample)
-                if filename in gtzan.filtered_valid:
-                    cls.validation.append(sample)
-                seed += 1
+        mocked_data = get_mock_dataset(cls.root_dir)
+        cls.samples = mocked_data[0]
+        cls.training = mocked_data[1]
+        cls.validation = mocked_data[2]
+        cls.testing = mocked_data[3]
 
     def test_no_subset(self):
         dataset = gtzan.GTZAN(self.root_dir)