formatting

BenAAndrew · Feb 6, 2022 · c62fdd0 · c62fdd0
1 parent b5b8438
commit c62fdd0
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Showing 5 changed files with 8 additions and 8 deletions.
diff --git a/application/views.py b/application/views.py
@@ -452,10 +452,10 @@ def label_clip():
 
     # Update dataset size
     update_dataset_info(
-        os.path.join(paths["datasets"], dataset, METADATA_FILE), 
+        os.path.join(paths["datasets"], dataset, METADATA_FILE),
         os.path.join(paths["datasets"], dataset, INFO_FILE),
         os.path.join(paths["datasets"], dataset, UNLABELLED_FOLDER, clip),
-        text
+        text,
     )
 
     # Add to metadata

diff --git a/synthesis/vocoders/hifigan_model.py b/synthesis/vocoders/hifigan_model.py
@@ -169,7 +169,7 @@ def __init__(self, h):
             self.ups.append(
                 weight_norm(
                     ConvTranspose1d(
-                        h.upsample_initial_channel // (2 ** i),
+                        h.upsample_initial_channel // (2**i),
                         h.upsample_initial_channel // (2 ** (i + 1)),
                         k,
                         u,
@@ -358,7 +358,7 @@ def discriminator_loss(disc_real_outputs, disc_generated_outputs):
     g_losses = []
     for dr, dg in zip(disc_real_outputs, disc_generated_outputs):
         r_loss = torch.mean((1 - dr) ** 2)
-        g_loss = torch.mean(dg ** 2)
+        g_loss = torch.mean(dg**2)
         loss += r_loss + g_loss
         r_losses.append(r_loss.item())
         g_losses.append(g_loss.item())

diff --git a/tests/test_dataset.py b/tests/test_dataset.py
@@ -332,7 +332,7 @@ def test_update_dataset_info():
 
     with open(info_path) as f:
         info_before = json.load(f)
-    
+
     update_dataset_info(metadata_path, info_path, clip_path, text)
 
     with open(info_path) as f:

diff --git a/training/hifigan/models.py b/training/hifigan/models.py
@@ -169,7 +169,7 @@ def __init__(self, h):
             self.ups.append(
                 weight_norm(
                     ConvTranspose1d(
-                        h.upsample_initial_channel // (2 ** i),
+                        h.upsample_initial_channel // (2**i),
                         h.upsample_initial_channel // (2 ** (i + 1)),
                         k,
                         u,
@@ -359,7 +359,7 @@ def discriminator_loss(disc_real_outputs, disc_generated_outputs):
     g_losses = []
     for dr, dg in zip(disc_real_outputs, disc_generated_outputs):
         r_loss = torch.mean((1 - dr) ** 2)
-        g_loss = torch.mean(dg ** 2)
+        g_loss = torch.mean(dg**2)
         loss += r_loss + g_loss
         r_losses.append(r_loss.item())
         g_losses.append(g_loss.item())

diff --git a/training/tacotron2_model/stft.py b/training/tacotron2_model/stft.py
@@ -97,7 +97,7 @@ def transform(self, input_data):
         real_part = forward_transform[:, :cutoff, :]
         imag_part = forward_transform[:, cutoff:, :]
 
-        magnitude = torch.sqrt(real_part ** 2 + imag_part ** 2)
+        magnitude = torch.sqrt(real_part**2 + imag_part**2)
         phase = torch.autograd.Variable(torch.atan2(imag_part.data, real_part.data))
 
         return magnitude, phase