tests/unit/tts/test_losses.py: Add gradient tests and update precision calculation methods

- Change precision threshold to ’1e-5‘
- Use relative error instead of absolute error

tests/unit/tts/test_losses.py

@@ -10,6 +10,10 @@ def test_dac_losses():
         loss_origin = torch.load(f'tests/unit/tts/data/{i}-loss.pt')
         recons = AudioSignal(f'tests/unit/tts/data/{i}-recons.wav')
         signal = AudioSignal(f'tests/unit/tts/data/{i}-signal.wav')
+
+        recons.audio_data.stop_gradient = False
+        signal.audio_data.stop_gradient = False
+
         loss_fn_1 = MultiScaleSTFTLoss()
         loss_fn_2 = MultiMelSpectrogramLoss(
             n_mels=[5, 10, 20, 40, 80, 160, 320],
@@ -18,22 +22,57 @@ def test_dac_losses():
             pow=1.0,
             mel_fmin=[0, 0, 0, 0, 0, 0, 0],
             mel_fmax=[None, None, None, None, None, None, None])
+
         #
         # Test AudioSignal
         #
+
+        loss_1 = loss_fn_1(recons, signal)
+        loss_1.backward()
+        loss_1_grad = signal.audio_data.grad.sum()
+
+        assert abs((loss_1.item() - loss_origin['stft/loss'].item()) /
+                   loss_1.item()) < 1e-5
+        assert abs((loss_1_grad.item() - loss_origin['stft/grad'].sum().item())
+                   / loss_1_grad.item()) < 1e-5
+
+        signal.audio_data.clear_grad()
+        recons.audio_data.clear_grad()
+
+        loss_2 = loss_fn_2(recons, signal)
+        loss_2.backward()
+        loss_2_grad = signal.audio_data.grad.sum()
+
+        assert abs((loss_2.item() - loss_origin['mel/loss'].item()) /
+                   loss_2.item()) < 1e-5
         assert abs(
-            loss_fn_1(recons, signal).item() - loss_origin['stft/loss']
-            .item()) < 1e-5
-        assert abs(
-            loss_fn_2(recons, signal).item() - loss_origin['mel/loss']
-            .item()) < 1e-5
+            (signal.audio_data.grad.sum().item() -
+             loss_origin['mel/grad'].sum().item()) / loss_2_grad.item()) < 1e-5
+
+        signal.audio_data.clear_grad()
+        recons.audio_data.clear_grad()
 
         #
         # Test Tensor
         #
-        assert abs(
-            loss_fn_1(recons.audio_data, signal.audio_data).item() -
-            loss_origin['stft/loss'].item()) < 1e-3
-        assert abs(
-            loss_fn_2(recons.audio_data, signal.audio_data).item() -
-            loss_origin['mel/loss'].item()) < 1e-3
+
+        loss_1 = loss_fn_1(recons.audio_data, signal.audio_data)
+        loss_1.backward()
+        loss_1_grad = signal.audio_data.grad.sum()
+
+        assert abs(loss_1.item() - loss_origin['stft/loss']
+                   .item()) / loss_1.item() < 1e-5
+        assert abs(loss_1_grad.item() - loss_origin['stft/grad'].sum()
+                   .item()) / loss_1_grad.item() < 1e-5
+
+        signal.audio_data.clear_grad()
+        recons.audio_data.clear_grad()
+
+        loss_2 = loss_fn_2(recons.audio_data, signal.audio_data)
+        loss_2.backward()
+        loss_2_grad = signal.audio_data.grad.sum()
+
+        assert abs((loss_2.item() - loss_origin['mel/loss'].item()) /
+                   loss_2.item()) < 1e-5
+        assert abs((loss_2_grad.item() - loss_origin['mel/grad'].sum().item()) /
+                   loss_2_grad.item()) < 1e-5