Format code (#1162)

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

infer/lib/infer_pack/models.py

@@ -1,5 +1,6 @@
 import math
 import logging
+
 logger = logging.getLogger(__name__)
 
 import numpy as np
@@ -615,7 +616,9 @@ class SynthesizerTrnMs256NSFsid(nn.Module):
             inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
         )
         self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
-        logger.debug("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+        logger.debug(
+            "gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim
+        )
 
     def remove_weight_norm(self):
         self.dec.remove_weight_norm()
@@ -731,7 +734,9 @@ class SynthesizerTrnMs768NSFsid(nn.Module):
             inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
         )
         self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
-        logger.debug("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+        logger.debug(
+            "gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim
+        )
 
     def remove_weight_norm(self):
         self.dec.remove_weight_norm()
@@ -844,7 +849,9 @@ class SynthesizerTrnMs256NSFsid_nono(nn.Module):
             inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
         )
         self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
-        logger.debug("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+        logger.debug(
+            "gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim
+        )
 
     def remove_weight_norm(self):
         self.dec.remove_weight_norm()
@@ -950,7 +957,9 @@ class SynthesizerTrnMs768NSFsid_nono(nn.Module):
             inter_channels, hidden_channels, 5, 1, 3, gin_channels=gin_channels
         )
         self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
-        logger.debug("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+        logger.debug(
+            "gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim
+        )
 
     def remove_weight_norm(self):
         self.dec.remove_weight_norm()

infer/lib/infer_pack/models_onnx.py

@@ -1,5 +1,6 @@
 import math
 import logging
+
 logger = logging.getLogger(__name__)
 
 import numpy as np
@@ -619,7 +620,9 @@ class SynthesizerTrnMsNSFsidM(nn.Module):
         )
         self.emb_g = nn.Embedding(self.spk_embed_dim, gin_channels)
         self.speaker_map = None
-        logger.debug("gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim)
+        logger.debug(
+            "gin_channels:", gin_channels, "self.spk_embed_dim:", self.spk_embed_dim
+        )
 
     def remove_weight_norm(self):
         self.dec.remove_weight_norm()

infer/lib/infer_pack/onnx_inference.py

@@ -4,6 +4,7 @@ import onnxruntime
 import soundfile
 
 import logging
+
 logger = logging.getLogger(__name__)
 
 

infer/lib/train/data_utils.py

@@ -1,6 +1,7 @@
 import os
 import traceback
 import logging
+
 logger = logging.getLogger(__name__)
 
 import numpy as np

infer/lib/train/mel_processing.py

@@ -2,6 +2,7 @@ import torch
 import torch.utils.data
 from librosa.filters import mel as librosa_mel_fn
 import logging
+
 logger = logging.getLogger(__name__)
 
 MAX_WAV_VALUE = 32768.0

infer/modules/train/train.py

@@ -1,6 +1,7 @@
 import os
 import sys
 import logging
+
 logger = logging.getLogger(__name__)
 
 now_dir = os.getcwd()

infer/modules/uvr5/mdxnet.py

@@ -1,5 +1,6 @@
 import os
 import logging
+
 logger = logging.getLogger(__name__)
 
 import librosa

infer/modules/uvr5/modules.py

@@ -1,6 +1,7 @@
 import os
 import traceback
 import logging
+
 logger = logging.getLogger(__name__)
 
 import ffmpeg

infer/modules/uvr5/preprocess.py

@@ -1,5 +1,6 @@
 import os
 import logging
+
 logger = logging.getLogger(__name__)
 
 import librosa

infer/modules/vc/modules.py

@@ -1,5 +1,6 @@
 import traceback
 import logging
+
 logger = logging.getLogger(__name__)
 
 import numpy as np
@@ -52,8 +53,16 @@ class VC:
         if not sid:
             if self.hubert_model is not None:  # 考虑到轮询, 需要加个判断看是否 sid 是由有模型切换到无模型的
                 logger.info("Clean model cache")
-                del self.net_g, self.n_spk, self.vc, self.hubert_model, self.tgt_sr  # ,cpt
-                self.hubert_model = self.net_g = self.n_spk = self.vc = self.hubert_model = self.tgt_sr = None
+                del (
+                    self.net_g,
+                    self.n_spk,
+                    self.vc,
+                    self.hubert_model,
+                    self.tgt_sr,
+                )  # ,cpt
+                self.hubert_model = (
+                    self.net_g
+                ) = self.n_spk = self.vc = self.hubert_model = self.tgt_sr = None
                 if torch.cuda.is_available():
                     torch.cuda.empty_cache()
                 ###楼下不这么折腾清理不干净

infer/modules/vc/pipeline.py

@@ -2,6 +2,7 @@ import os
 import sys
 import traceback
 import logging
+
 logger = logging.getLogger(__name__)
 
 from functools import lru_cache
@@ -267,9 +268,7 @@ class Pipeline(object):
         with torch.no_grad():
             hasp = pitch is not None and pitchf is not None
             arg = (feats, p_len, pitch, pitchf, sid) if hasp else (feats, p_len, sid)
-            audio1 = (
-                (net_g.infer(*arg)[0][0, 0]).data.cpu().float().numpy()
-            )
+            audio1 = (net_g.infer(*arg)[0][0, 0]).data.cpu().float().numpy()
             del hasp, arg
         del feats, p_len, padding_mask
         if torch.cuda.is_available():

infer/modules/vc/utils.py

@@ -2,6 +2,7 @@ import os
 
 from fairseq import checkpoint_utils
 
+
 def get_index_path_from_model(sid):
     return next(
         (