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