Merge pull request #837 from IAHispano/formatter/main

chore(format): run black on main
IAHispano · Oct 26, 2024 · e8383ce · e8383ce
2 parents 5ebc144 + 90a2e40
commit e8383ce
Showing 1 changed file with 11 additions and 8 deletions.
diff --git a/rvc/train/train.py b/rvc/train/train.py
@@ -248,7 +248,7 @@ def continue_overtrain_detector(training_file_path):
 
     if cleanup:
         print("Removing files from the prior training attempt...")
-        
+
         # Clean up unnecessary files
         for root, dirs, files in os.walk(
             os.path.join(now_dir, "logs", model_name), topdown=False
@@ -273,10 +273,11 @@ def continue_overtrain_detector(training_file_path):
                     os.rmdir(folder_path)
 
         print("Cleanup done!")
-        
+
     continue_overtrain_detector(training_file_path)
     start()
 
+
 def run(
     rank,
     n_gpus,
@@ -675,7 +676,9 @@ def train_and_evaluate(
                 y_d_hat_r, y_d_hat_g, fmap_r, fmap_g = net_d(wave, y_hat)
                 with autocast(enabled=False):
                     loss_mel = F.l1_loss(y_mel, y_hat_mel) * config.train.c_mel
-                    loss_kl = kl_loss(z_p, logs_q, m_p, logs_p, z_mask) * config.train.c_kl
+                    loss_kl = (
+                        kl_loss(z_p, logs_q, m_p, logs_p, z_mask) * config.train.c_kl
+                    )
                     loss_fm = feature_loss(fmap_r, fmap_g)
                     loss_gen, losses_gen = generator_loss(y_d_hat_g)
                     loss_gen_all = loss_gen + loss_fm + loss_mel + loss_kl
@@ -717,11 +720,11 @@ def train_and_evaluate(
             "loss/g/mel": loss_mel,
             "loss/g/kl": loss_kl,
         }
-        # commented out 
-        #scalar_dict.update({f"loss/g/{i}": v for i, v in enumerate(losses_gen)})
-        #scalar_dict.update({f"loss/d_r/{i}": v for i, v in enumerate(losses_disc_r)})
-        #scalar_dict.update({f"loss/d_g/{i}": v for i, v in enumerate(losses_disc_g)})
-            
+        # commented out
+        # scalar_dict.update({f"loss/g/{i}": v for i, v in enumerate(losses_gen)})
+        # scalar_dict.update({f"loss/d_r/{i}": v for i, v in enumerate(losses_disc_r)})
+        # scalar_dict.update({f"loss/d_g/{i}": v for i, v in enumerate(losses_disc_g)})
+
         image_dict = {
             "slice/mel_org": plot_spectrogram_to_numpy(y_mel[0].data.cpu().numpy()),
             "slice/mel_gen": plot_spectrogram_to_numpy(y_hat_mel[0].data.cpu().numpy()),