test melgan feature loss

tests/test_vocoder_losses.py

@@ -5,7 +5,7 @@ from tests import get_tests_input_path, get_tests_output_path, get_tests_path
 
 from TTS.utils.audio import AudioProcessor
 from TTS.utils.io import load_config
-from TTS.vocoder.layers.losses import MultiScaleSTFTLoss, STFTLoss, TorchSTFT
+from TTS.vocoder.layers.losses import MultiScaleSTFTLoss, STFTLoss, TorchSTFT, MelganFeatureLoss
 
 TESTS_PATH = get_tests_path()
 
@@ -52,3 +52,41 @@ def test_multiscale_stft_loss():
     loss_m, loss_sc = stft_loss(wav, torch.rand_like(wav))
     assert loss_sc < 1.0
     assert loss_m + loss_sc > 0
+
+def test_melgan_feature_loss():
+    feats_real = []
+    feats_fake = []
+
+    # if all the features are different.
+    for _ in range(5):  # different scales
+        scale_feats_real = []
+        scale_feats_fake = []
+        for _ in range(4):  # different layers
+            scale_feats_real.append(torch.rand([3, 5, 7]))
+            scale_feats_fake.append(torch.rand([3, 5, 7]))
+        feats_real.append(scale_feats_real)
+        feats_fake.append(scale_feats_fake)
+
+    loss_func = MelganFeatureLoss()
+    loss = loss_func(feats_fake, feats_real)
+    assert loss.item() <= 1.0
+
+
+    feats_real = []
+    feats_fake = []
+
+    # if all the features are the same
+    for _ in range(5):  # different scales
+        scale_feats_real = []
+        scale_feats_fake = []
+        for _ in range(4):  # different layers
+            tensor = torch.rand([3, 5, 7])
+            scale_feats_real.append(tensor)
+            scale_feats_fake.append(tensor)
+        feats_real.append(scale_feats_real)
+        feats_fake.append(scale_feats_fake)
+
+    loss_func = MelganFeatureLoss()
+    loss = loss_func(feats_fake, feats_real)
+    assert loss.item() == 0
+