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rvc/configs/config.py

@@ -137,6 +137,7 @@ class Config:
 
         return x_pad, x_query, x_center, x_max
 
+
 def max_vram_gpu(gpu):
     if torch.cuda.is_available():
         gpu_properties = torch.cuda.get_device_properties(gpu)
@@ -144,7 +145,8 @@ def max_vram_gpu(gpu):
         return total_memory_gb
     else:
         return "0"
-    
+
+
 def get_gpu_info():
     ngpu = torch.cuda.device_count()
     gpu_infos = []
@@ -159,7 +161,5 @@ def get_gpu_info():
     if len(gpu_infos) > 0:
         gpu_info = "\n".join(gpu_infos)
     else:
-        gpu_info = (
-            "Unfortunately, there is no compatible GPU available to support your training."
-        )
-    return gpu_info
+        gpu_info = "Unfortunately, there is no compatible GPU available to support your training."
+    return gpu_info

rvc/train/extract/extract_f0_print.py

@@ -48,9 +48,11 @@ class FeatureInput:
         torch_device = (
             torch.device(f"cuda:{torch_device_index % torch.cuda.device_count()}")
             if torch.cuda.is_available()
-            else torch.device("mps")
-            if torch.backends.mps.is_available()
-            else torch.device("cpu")
+            else (
+                torch.device("mps")
+                if torch.backends.mps.is_available()
+                else torch.device("cpu")
+            )
         )
 
         audio = torch.from_numpy(x.astype(np.float32)).to(torch_device, copy=True)

rvc/train/losses.py

@@ -1,5 +1,6 @@
 import torch
 
+
 def feature_loss(fmap_r, fmap_g):
     loss = 0
     for dr, dg in zip(fmap_r, fmap_g):

rvc/train/process/change_info.py

@@ -1,6 +1,7 @@
 import os
 import torch
 
+
 def change_info(path, info, name):
     try:
         ckpt = torch.load(path, map_location="cpu")
@@ -10,4 +11,4 @@ def change_info(path, info, name):
         torch.save(ckpt, f"logs/{name}/{name}")
         return "Success."
     except Exception as error:
-        print(error)
+        print(error)