chore(format): run black on dev

configs/config.py

@@ -263,6 +263,7 @@ class Config:
         )
         return x_pad, x_query, x_center, x_max
 
+
 @singleton_variable
 class CPUConfig:
     def __init__(self):

infer-web.py

@@ -664,7 +664,11 @@ def train_index(exp_dir1, version19):
     for i in range(0, big_npy.shape[0], batch_size_add):
         index.add(big_npy[i : i + batch_size_add])
     index_save_path = "%s/added_IVF%s_Flat_nprobe_%s_%s_%s.index" % (
-        exp_dir, n_ivf, index_ivf.nprobe, exp_dir1, version19
+        exp_dir,
+        n_ivf,
+        index_ivf.nprobe,
+        exp_dir1,
+        version19,
     )
     faiss.write_index(index, index_save_path)
     infos.append(i18n("成功构建索引到") + " " + index_save_path)
@@ -1640,11 +1644,13 @@ with gr.Blocks(title="RVC WebUI") as app:
 
 try:
     import signal
+
     def cleanup(signum, frame):
         signame = signal.Signals(signum).name
-        print(f'Got signal {signame} ({signum})')
+        print(f"Got signal {signame} ({signum})")
         app.close()
         sys.exit(0)
+
     signal.signal(signal.SIGINT, cleanup)
     signal.signal(signal.SIGTERM, cleanup)
     if config.iscolab:

infer/lib/train/utils.py

@@ -66,6 +66,7 @@ def load_checkpoint_d(checkpoint_path, combd, sbd, optimizer=None, load_opt=1):
     return model, optimizer, learning_rate, iteration
 """
 
+
 def load_checkpoint(checkpoint_path, model, optimizer=None, load_opt=1):
     assert os.path.isfile(checkpoint_path)
     checkpoint_dict = torch.load(checkpoint_path, map_location="cpu")
@@ -130,6 +131,7 @@ def save_checkpoint(model, optimizer, learning_rate, iteration, checkpoint_path)
         checkpoint_path,
     )
 
+
 """
 def save_checkpoint_d(combd, sbd, optimizer, learning_rate, iteration, checkpoint_path):
     logger.info(
@@ -157,6 +159,7 @@ def save_checkpoint_d(combd, sbd, optimizer, learning_rate, iteration, checkpoin
     )
 """
 
+
 def summarize(
     writer,
     global_step,

infer/modules/vc/hash.py

@@ -27,18 +27,22 @@ class TorchSeedContext:
 half_hash_len = 512
 expand_factor = 65536 * 8
 
+
 @singleton_variable
 def original_audio_storage():
     return np.load(pathlib.Path(__file__).parent / "lgdsng.npz")
 
+
 @singleton_variable
 def original_audio():
     return original_audio_storage()["a"]
 
+
 @singleton_variable
 def original_audio_time_minus():
     return original_audio_storage()["t"]
 
+
 @singleton_variable
 def original_audio_freq_minus():
     return original_audio_storage()["f"]