fix: 卸载音色省显存

顺便将所有print换成了统一的logger
2025-12-16 11:48:08 +01:00 · 2023-09-01 15:18:08 +08:00
parent 8d5a77dbe9
commit 04a33b9709
23 changed files with 189 additions and 106 deletions
--- a/tools/app.py
+++ b/tools/app.py
@@ -13,9 +13,10 @@ logging.getLogger("numba").setLevel(logging.WARNING)
 logging.getLogger("markdown_it").setLevel(logging.WARNING)
 logging.getLogger("urllib3").setLevel(logging.WARNING)
 logging.getLogger("matplotlib").setLevel(logging.WARNING)
+logger = logging.getLogger(__name__)

 i18n = I18nAuto()
-i18n.print()
+logger.info(i18n)

 load_dotenv()
 config = Config()
--- a/tools/calc_rvc_model_similarity.py
+++ b/tools/calc_rvc_model_similarity.py
@@ -1,7 +1,8 @@
 # This code references https://huggingface.co/JosephusCheung/ASimilarityCalculatior/blob/main/qwerty.py
 # Fill in the path of the model to be queried and the root directory of the reference models, and this script will return the similarity between the model to be queried and all reference models.
 import os
-import sys
+import logging
+logger = logging.getLogger(__name__)

 import torch
 import torch.nn as nn
@@ -55,7 +56,7 @@ def main(path, root):
    torch.manual_seed(114514)
    model_a = torch.load(path, map_location="cpu")["weight"]

-    print("Query:\t\t%s\t%s" % (path, model_hash(path)))
+    logger.info("Query:\t\t%s\t%s" % (path, model_hash(path)))

    map_attn_a = {}
    map_rand_input = {}
@@ -82,7 +83,7 @@ def main(path, root):
            sim = torch.mean(torch.cosine_similarity(attn_a, attn_b))
            sims.append(sim)

-        print(
+        logger.info(
            "Reference:\t%s\t%s\t%s"
            % (path, model_hash(path), f"{torch.mean(torch.stack(sims)) * 1e2:.2f}%")
        )
--- a/tools/infer/infer-pm-index256.py
+++ b/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)  #
--- a/tools/infer/train-index-v2.py
+++ b/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])
--- a/tools/infer/train-index.py
+++ b/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")
 """
--- a/tools/rvc_for_realtime.py
+++ b/tools/rvc_for_realtime.py
@@ -1,6 +1,9 @@
 import os
 import sys
 import traceback
+import logging
+logger = logging.getLogger(__name__)
+
 from time import time as ttime

 import fairseq
@@ -67,7 +70,7 @@ class RVC:
            if index_rate != 0:
                self.index = faiss.read_index(index_path)
                self.big_npy = self.index.reconstruct_n(0, self.index.ntotal)
-                print("Index search enabled")
+                logger.info("Index search enabled")
            self.index_path = index_path
            self.index_rate = index_rate
            models, _, _ = fairseq.checkpoint_utils.load_model_ensemble_and_task(
@@ -102,7 +105,7 @@ class RVC:
                else:
                    self.net_g = SynthesizerTrnMs768NSFsid_nono(*cpt["config"])
            del self.net_g.enc_q
-            print(self.net_g.load_state_dict(cpt["weight"], strict=False))
+            logger.debug(self.net_g.load_state_dict(cpt["weight"], strict=False))
            self.net_g.eval().to(device)
            # print(2333333333,device,config.device,self.device)#net_g是device，hubert是config.device
            if config.is_half:
@@ -111,7 +114,7 @@ class RVC:
                self.net_g = self.net_g.float()
            self.is_half = config.is_half
        except:
-            print(traceback.format_exc())
+            logger.warn(traceback.format_exc())

    def change_key(self, new_key):
        self.f0_up_key = new_key
@@ -120,7 +123,7 @@ class RVC:
        if new_index_rate != 0 and self.index_rate == 0:
            self.index = faiss.read_index(self.index_path)
            self.big_npy = self.index.reconstruct_n(0, self.index.ntotal)
-            print("Index search enabled")
+            logger.info("Index search enabled")
        self.index_rate = new_index_rate

    def get_f0_post(self, f0):
@@ -237,7 +240,7 @@ class RVC:
        if hasattr(self, "model_rmvpe") == False:
            from infer.lib.rmvpe import RMVPE

-            print("Loading rmvpe model")
+            logger.info("Loading rmvpe model")
            self.model_rmvpe = RMVPE(
                # "rmvpe.pt", is_half=self.is_half if self.device.type!="privateuseone" else False, device=self.device if self.device.type!="privateuseone"else "cpu"####dml时强制对rmvpe用cpu跑
                #  "rmvpe.pt", is_half=False, device=self.device####dml配置
@@ -295,10 +298,10 @@ class RVC:
                    + (1 - self.index_rate) * feats[0][-leng_replace_head:]
                )
            else:
-                print("Index search FAILED or disabled")
+                logger.warn("Index search FAILED or disabled")
        except:
            traceback.print_exc()
-            print("Index search FAILED")
+            logger.warn("Index search FAILED")
        feats = F.interpolate(feats.permute(0, 2, 1), scale_factor=2).permute(0, 2, 1)
        t3 = ttime()
        if self.if_f0 == 1:
@@ -338,5 +341,5 @@ class RVC:
                    .float()
                )
        t5 = ttime()
-        print("Spent time: fea =", t2 - t1, ", index =", t3 - t2, ", f0 =", t4 - t3, ", model =", t5 - t4)
+        logger.info("Spent time: fea =", t2 - t1, ", index =", t3 - t2, ", f0 =", t4 - t3, ", model =", t5 - t4)
        return infered_audio