optimize: move slicer2, rmvpe, my_utils to lib

extract_f0_print.py

@@ -2,7 +2,7 @@ import os, traceback, sys, parselmouth
 
 now_dir = os.getcwd()
 sys.path.append(now_dir)
-from my_utils import load_audio
+from lib.audio import load_audio
 import pyworld
 import numpy as np, logging
 

infer-web.py

@@ -33,7 +33,7 @@ from lib.infer_pack.models import (
 )
 from lib.infer_pack.models_onnx import SynthesizerTrnMsNSFsidM
 from infer_uvr5 import _audio_pre_, _audio_pre_new
-from my_utils import load_audio
+from lib.audio import load_audio
 from lib.train.process_ckpt import change_info, extract_small_model, merge, show_info
 from vc_infer_pipeline import VC
 from sklearn.cluster import MiniBatchKMeans

infer_batch_rvc.py

@@ -116,7 +116,7 @@ from lib.infer_pack.models import (
     SynthesizerTrnMs768NSFsid,
     SynthesizerTrnMs768NSFsid_nono,
 )
-from my_utils import load_audio
+from lib.audio import load_audio
 from fairseq import checkpoint_utils
 from scipy.io import wavfile
 

lib/rmvpe.py

@@ -1,6 +1,5 @@
-import sys, torch, numpy as np, traceback, pdb
+import torch, numpy as np
 import torch.nn as nn
-from time import time as ttime
 import torch.nn.functional as F
 
 
@@ -247,7 +246,7 @@ class E2E(nn.Module):
             )
         else:
             self.fc = nn.Sequential(
-                nn.Linear(3 * N_MELS, N_CLASS), nn.Dropout(0.25), nn.Sigmoid()
+                nn.Linear(3 * nn.N_MELS, nn.N_CLASS), nn.Dropout(0.25), nn.Sigmoid()
             )
 
     def forward(self, mel):

rvc_for_realtime.py

@@ -196,7 +196,7 @@ class RVC:
 
     def get_f0_rmvpe(self, x, f0_up_key):
         if hasattr(self, "model_rmvpe") == False:
-            from rmvpe import RMVPE
+            from lib.rmvpe import RMVPE
 
             print("loading rmvpe model")
             self.model_rmvpe = RMVPE(

trainset_preprocess_pipeline_print.py

@@ -10,11 +10,11 @@ n_p = int(sys.argv[3])
 exp_dir = sys.argv[4]
 noparallel = sys.argv[5] == "True"
 import numpy as np, os, traceback
-from slicer2 import Slicer
+from lib.slicer2 import Slicer
 import librosa, traceback
 from scipy.io import wavfile
 import multiprocessing
-from my_utils import load_audio
+from lib.audio import load_audio
 
 mutex = multiprocessing.Lock()
 f = open("%s/preprocess.log" % exp_dir, "a+")

vc_infer_pipeline.py

@@ -129,7 +129,7 @@ class VC(object):
             f0 = f0[0].cpu().numpy()
         elif f0_method == "rmvpe":
             if hasattr(self, "model_rmvpe") == False:
-                from rmvpe import RMVPE
+                from lib.rmvpe import RMVPE
 
                 print("loading rmvpe model")
                 self.model_rmvpe = RMVPE(