Format code (#624)

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

config.py

@@ -58,12 +58,13 @@ class Config:
             cmd_opts.noparallel,
             cmd_opts.noautoopen,
         )
-    
+
     # has_mps is only available in nightly pytorch (for now) and MasOS 12.3+.
     # check `getattr` and try it for compatibility
     @staticmethod
     def has_mps() -> bool:
-        if not torch.backends.mps.is_available(): return False
+        if not torch.backends.mps.is_available():
+            return False
         try:
             torch.zeros(1).to(torch.device("mps"))
             return True

extract_feature_print.py

@@ -1,6 +1,6 @@
 import os, sys, traceback
 
-os.environ['PYTORCH_ENABLE_MPS_FALLBACK'] = '1'
+os.environ["PYTORCH_ENABLE_MPS_FALLBACK"] = "1"
 
 # device=sys.argv[1]
 n_part = int(sys.argv[2])

infer-web.py

@@ -43,7 +43,9 @@ logging.getLogger("numba").setLevel(logging.WARNING)
 
 tmp = os.path.join(now_dir, "TEMP")
 shutil.rmtree(tmp, ignore_errors=True)
-shutil.rmtree("%s/runtime/Lib/site-packages/lib.infer_pack" % (now_dir), ignore_errors=True)
+shutil.rmtree(
+    "%s/runtime/Lib/site-packages/lib.infer_pack" % (now_dir), ignore_errors=True
+)
 shutil.rmtree("%s/runtime/Lib/site-packages/uvr5_pack" % (now_dir), ignore_errors=True)
 os.makedirs(tmp, exist_ok=True)
 os.makedirs(os.path.join(now_dir, "logs"), exist_ok=True)
@@ -328,6 +330,7 @@ def uvr(model_name, inp_root, save_root_vocal, paths, save_root_ins, agg, format
         )
         if model_name == "onnx_dereverb_By_FoxJoy":
             from MDXNet import MDXNetDereverb
+
             pre_fun = MDXNetDereverb(15)
         else:
             func = _audio_pre_ if "DeEcho" not in model_name else _audio_pre_new

lib/infer_pack/onnx_inference.py

@@ -39,7 +39,9 @@ def get_f0_predictor(f0_predictor, hop_length, sampling_rate, **kargs):
             hop_length=hop_length, sampling_rate=sampling_rate
         )
     elif f0_predictor == "harvest":
-        from lib.infer_pack.modules.F0Predictor.HarvestF0Predictor import HarvestF0Predictor
+        from lib.infer_pack.modules.F0Predictor.HarvestF0Predictor import (
+            HarvestF0Predictor,
+        )
 
         f0_predictor_object = HarvestF0Predictor(
             hop_length=hop_length, sampling_rate=sampling_rate