fix: 卸载音色省显存

顺便将所有print换成了统一的logger

tools/infer/infer-pm-index256.py

@@ -3,7 +3,8 @@
 对源特征进行检索
 """
 import os
-import pdb
+import logging
+logger = logging.getLogger(__name__)
 
 import parselmouth
 import torch
@@ -15,7 +16,6 @@ from time import time as ttime
 # import pyworld
 import librosa
 import numpy as np
-import scipy.signal as signal
 import soundfile as sf
 import torch.nn.functional as F
 from fairseq import checkpoint_utils
@@ -34,7 +34,7 @@ from scipy.io import wavfile
 
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 model_path = r"E:\codes\py39\vits_vc_gpu_train\assets\hubert\hubert_base.pt"  #
-print("Load model(s) from {}".format(model_path))
+logger.info("Load model(s) from {}".format(model_path))
 models, saved_cfg, task = checkpoint_utils.load_model_ensemble_and_task(
     [model_path],
     suffix="",
@@ -77,7 +77,7 @@ net_g = SynthesizerTrn256(
 # weights=torch.load("infer/ft-mi-freeze-vocoder_true_1k.pt")
 # weights=torch.load("infer/ft-mi-sim1k.pt")
 weights = torch.load("infer/ft-mi-no_opt-no_dropout.pt")
-print(net_g.load_state_dict(weights, strict=True))
+logger.debug(net_g.load_state_dict(weights, strict=True))
 
 net_g.eval().to(device)
 net_g.half()
@@ -198,4 +198,4 @@ for idx, name in enumerate(
     wavfile.write("ft-mi-no_opt-no_dropout-%s.wav" % name, 40000, audio)  ##
 
 
-print(ta0, ta1, ta2)  #
+logger.debug(ta0, ta1, ta2)  #

tools/infer/train-index-v2.py

@@ -3,6 +3,9 @@
 """
 import os
 import traceback
+import logging
+logger = logging.getLogger(__name__)
+
 from multiprocessing import cpu_count
 
 import faiss
@@ -23,11 +26,11 @@ big_npy = np.concatenate(npys, 0)
 big_npy_idx = np.arange(big_npy.shape[0])
 np.random.shuffle(big_npy_idx)
 big_npy = big_npy[big_npy_idx]
-print(big_npy.shape)  # (6196072, 192)#fp32#4.43G
+logger.debug(big_npy.shape)  # (6196072, 192)#fp32#4.43G
 if big_npy.shape[0] > 2e5:
     # if(1):
     info = "Trying doing kmeans %s shape to 10k centers." % big_npy.shape[0]
-    print(info)
+    logger.info(info)
     try:
         big_npy = (
             MiniBatchKMeans(
@@ -42,7 +45,7 @@ if big_npy.shape[0] > 2e5:
         )
     except:
         info = traceback.format_exc()
-        print(info)
+        logger.warn(info)
 
 np.save("tools/infer/big_src_feature_mi.npy", big_npy)
 
@@ -50,14 +53,14 @@ np.save("tools/infer/big_src_feature_mi.npy", big_npy)
 # big_npy=np.load("/bili-coeus/jupyter/jupyterhub-liujing04/vits_ch/inference_f0/big_src_feature_mi.npy")
 n_ivf = min(int(16 * np.sqrt(big_npy.shape[0])), big_npy.shape[0] // 39)
 index = faiss.index_factory(768, "IVF%s,Flat" % n_ivf)  # mi
-print("Training...")
+logger.info("Training...")
 index_ivf = faiss.extract_index_ivf(index)  #
 index_ivf.nprobe = 1
 index.train(big_npy)
 faiss.write_index(
     index, "tools/infer/trained_IVF%s_Flat_baseline_src_feat_v2.index" % (n_ivf)
 )
-print("Adding...")
+logger.info("Adding...")
 batch_size_add = 8192
 for i in range(0, big_npy.shape[0], batch_size_add):
     index.add(big_npy[i : i + batch_size_add])

tools/infer/train-index.py

@@ -2,6 +2,8 @@
 格式：直接cid为自带的index位；aid放不下了，通过字典来查，反正就5w个
 """
 import os
+import logging
+logger = logging.getLogger(__name__)
 
 import faiss
 import numpy as np
@@ -13,19 +15,19 @@ for name in sorted(list(os.listdir(inp_root))):
     phone = np.load("%s/%s" % (inp_root, name))
     npys.append(phone)
 big_npy = np.concatenate(npys, 0)
-print(big_npy.shape)  # (6196072, 192)#fp32#4.43G
+logger.debug(big_npy.shape)  # (6196072, 192)#fp32#4.43G
 np.save("infer/big_src_feature_mi.npy", big_npy)
 
 ##################train+add
 # big_npy=np.load("/bili-coeus/jupyter/jupyterhub-liujing04/vits_ch/inference_f0/big_src_feature_mi.npy")
-print(big_npy.shape)
+logger.debug(big_npy.shape)
 index = faiss.index_factory(256, "IVF512,Flat")  # mi
-print("Training...")
+logger.info("Training...")
 index_ivf = faiss.extract_index_ivf(index)  #
 index_ivf.nprobe = 9
 index.train(big_npy)
 faiss.write_index(index, "infer/trained_IVF512_Flat_mi_baseline_src_feat.index")
-print("Adding...")
+logger.info("Adding...")
 index.add(big_npy)
 faiss.write_index(index, "infer/added_IVF512_Flat_mi_baseline_src_feat.index")
 """