fix: 卸载音色省显存

顺便将所有print换成了统一的logger

infer/modules/uvr5/mdxnet.py

@@ -1,4 +1,6 @@
 import os
+import logging
+logger = logging.getLogger(__name__)
 
 import librosa
 import numpy as np
@@ -88,7 +90,7 @@ class Predictor:
     def __init__(self, args):
         import onnxruntime as ort
 
-        print(ort.get_available_providers())
+        logger.info(ort.get_available_providers())
         self.args = args
         self.model_ = get_models(
             device=cpu, dim_f=args.dim_f, dim_t=args.dim_t, n_fft=args.n_fft
@@ -101,7 +103,7 @@ class Predictor:
                 "CPUExecutionProvider",
             ],
         )
-        print("ONNX load done")
+        logger.info("ONNX load done")
 
     def demix(self, mix):
         samples = mix.shape[-1]

infer/modules/uvr5/modules.py

@@ -1,5 +1,7 @@
 import os
 import traceback
+import logging
+logger = logging.getLogger(__name__)
 
 import ffmpeg
 import torch
@@ -92,5 +94,5 @@ def uvr(model_name, inp_root, save_root_vocal, paths, save_root_ins, agg, format
             traceback.print_exc()
         if torch.cuda.is_available():
             torch.cuda.empty_cache()
-            print("Executed torch.cuda.empty_cache()")
+            logger.info("Executed torch.cuda.empty_cache()")
     yield "\n".join(infos)

infer/modules/uvr5/preprocess.py

@@ -1,4 +1,6 @@
 import os
+import logging
+logger = logging.getLogger(__name__)
 
 import librosa
 import numpy as np
@@ -116,7 +118,7 @@ class AudioPre:
                 )
             else:
                 wav_instrument = spec_utils.cmb_spectrogram_to_wave(y_spec_m, self.mp)
-            print("%s instruments done" % name)
+            logger.info("%s instruments done" % name)
             if format in ["wav", "flac"]:
                 sf.write(
                     os.path.join(
@@ -150,7 +152,7 @@ class AudioPre:
                 )
             else:
                 wav_vocals = spec_utils.cmb_spectrogram_to_wave(v_spec_m, self.mp)
-            print("%s vocals done" % name)
+            logger.info("%s vocals done" % name)
             if format in ["wav", "flac"]:
                 sf.write(
                     os.path.join(
@@ -283,7 +285,7 @@ class AudioPreDeEcho:
                 )
             else:
                 wav_instrument = spec_utils.cmb_spectrogram_to_wave(y_spec_m, self.mp)
-            print("%s instruments done" % name)
+            logger.info("%s instruments done" % name)
             if format in ["wav", "flac"]:
                 sf.write(
                     os.path.join(
@@ -317,7 +319,7 @@ class AudioPreDeEcho:
                 )
             else:
                 wav_vocals = spec_utils.cmb_spectrogram_to_wave(v_spec_m, self.mp)
-            print("%s vocals done" % name)
+            logger.info("%s vocals done" % name)
             if format in ["wav", "flac"]:
                 sf.write(
                     os.path.join(