What is the reason for this, please

C:\rvc\RVC1006Nvidia>runtime\python.exe infer-web.py --pycmd runtime\python.exe --port 7897
2024-08-20 14:22:23 | INFO | configs.config | Found GPU NVIDIA GeForce RTX 4050 Laptop GPU
is_half:True, device:cuda:0
2024-08-20 14:22:27 | INFO | main | Use Language: zh_CN
Running on local URL: http://0.0.0.0:7897
2024-08-20 14:23:17 | INFO | main | "runtime\python.exe" infer/modules/train/preprocess.py "D:\shuchuyuansheng" 40000 8 "C:\rvc\RVC1006Nvidia/logs/fx" False 3.0
['infer/modules/train/preprocess.py', 'D:\shuchuyuansheng', '40000', '8', 'C:\rvc\RVC1006Nvidia/logs/fx', 'False', '3.0']
start preprocess
['infer/modules/train/preprocess.py', 'D:\shuchuyuansheng', '40000', '8', 'C:\rvc\RVC1006Nvidia/logs/fx', 'False', '3.0']
['C:\rvc\RVC1006Nvidia\infer\modules\train\preprocess.py', 'D:\shuchuyuansheng', '40000', '8', 'C:\rvc\RVC1006Nvidia/logs/fx', 'False', '3.0']
['C:\rvc\RVC1006Nvidia\infer\modules\train\preprocess.py', 'D:\shuchuyuansheng', '40000', '8', 'C:\rvc\RVC1006Nvidia/logs/fx', 'False', '3.0']
['C:\rvc\RVC1006Nvidia\infer\modules\train\preprocess.py', 'D:\shuchuyuansheng', '40000', '8', 'C:\rvc\RVC1006Nvidia/logs/fx', 'False', '3.0']
['C:\rvc\RVC1006Nvidia\infer\modules\train\preprocess.py', 'D:\shuchuyuansheng', '40000', '8', 'C:\rvc\RVC1006Nvidia/logs/fx', 'False', '3.0']
['C:\rvc\RVC1006Nvidia\infer\modules\train\preprocess.py', 'D:\shuchuyuansheng', '40000', '8', 'C:\rvc\RVC1006Nvidia/logs/fx', 'False', '3.0']
['C:\rvc\RVC1006Nvidia\infer\modules\train\preprocess.py', 'D:\shuchuyuansheng', '40000', '8', 'C:\rvc\RVC1006Nvidia/logs/fx', 'False', '3.0']
['C:\rvc\RVC1006Nvidia\infer\modules\train\preprocess.py', 'D:\shuchuyuansheng', '40000', '8', 'C:\rvc\RVC1006Nvidia/logs/fx', 'False', '3.0']
['C:\rvc\RVC1006Nvidia\infer\modules\train\preprocess.py', 'D:\shuchuyuansheng', '40000', '8', 'C:\rvc\RVC1006Nvidia/logs/fx', 'False', '3.0']
D:\shuchuyuansheng/1_lfjq7-njb28-001_(Vocals).wav->Suc.
D:\shuchuyuansheng/fx.wav->Suc.
D:\shuchuyuansheng/jiebudiaoni.wav->Suc.
end preprocess
2024-08-20 14:23:30 | INFO | main | start preprocess
['infer/modules/train/preprocess.py', 'D:\shuchuyuansheng', '40000', '8', 'C:\rvc\RVC1006Nvidia/logs/fx', 'False', '3.0']
D:\shuchuyuansheng/1_lfjq7-njb28-001_(Vocals).wav->Suc.
D:\shuchuyuansheng/fx.wav->Suc.
D:\shuchuyuansheng/jiebudiaoni.wav->Suc.
end preprocess

2024-08-20 14:26:07 | INFO | main | "runtime\python.exe" infer/modules/train/extract/extract_f0_rmvpe.py 2 0 0 "C:\rvc\RVC1006Nvidia/logs/fx" True
2024-08-20 14:26:07 | INFO | main | "runtime\python.exe" infer/modules/train/extract/extract_f0_rmvpe.py 2 1 0 "C:\rvc\RVC1006Nvidia/logs/fx" True
['infer/modules/train/extract/extract_f0_rmvpe.py', '2', '1', '0', 'C:\rvc\RVC1006Nvidia/logs/fx', 'True']
['infer/modules/train/extract/extract_f0_rmvpe.py', '2', '0', '0', 'C:\rvc\RVC1006Nvidia/logs/fx', 'True']
todo-f0-18
todo-f0-18
f0ing,now-0,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_1.wav
f0ing,now-0,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_0.wav
Loading rmvpe model
Loading rmvpe model
f0ing,now-3,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_4.wav
f0ing,now-3,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_5.wav
f0ing,now-6,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_1.wav
f0ing,now-6,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_11.wav
f0ing,now-9,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_6.wav
f0ing,now-12,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_12.wav
f0ing,now-9,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_7.wav
f0ing,now-15,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_4.wav
f0ing,now-12,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_13.wav
f0ing,now-15,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_5.wav
2024-08-20 14:26:24 | INFO | main | ['infer/modules/train/extract/extract_f0_rmvpe.py', '2', '0', '0', 'C:\rvc\RVC1006Nvidia/logs/fx', 'True']
todo-f0-18
todo-f0-18
f0ing,now-0,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_1.wav
f0ing,now-0,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_0.wav
f0ing,now-3,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_4.wav
f0ing,now-3,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_5.wav
f0ing,now-6,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_1.wav
f0ing,now-6,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_11.wav
f0ing,now-9,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_6.wav
f0ing,now-12,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_12.wav
f0ing,now-9,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_7.wav
f0ing,now-15,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_4.wav
f0ing,now-12,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_13.wav
f0ing,now-15,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_5.wav

2024-08-20 14:26:24 | INFO | main | "runtime\python.exe" infer/modules/train/extract_feature_print.py cuda:0 1 0 0 "C:\rvc\RVC1006Nvidia/logs/fx" v2
['infer/modules/train/extract_feature_print.py', 'cuda:0', '1', '0', '0', 'C:\rvc\RVC1006Nvidia/logs/fx', 'v2']
C:\rvc\RVC1006Nvidia/logs/fx
load model(s) from assets/hubert/hubert_base.pt
move model to cuda
all-feature-36
now-36,all-0,0_0.wav,(149, 768)
now-36,all-3,0_11.wav,(67, 768)
now-36,all-6,0_4.wav,(149, 768)
now-36,all-9,0_7.wav,(149, 768)
now-36,all-12,1_1.wav,(149, 768)
now-36,all-15,1_3.wav,(149, 768)
now-36,all-18,1_6.wav,(149, 768)
now-36,all-21,1_9.wav,(149, 768)
now-36,all-24,2_12.wav,(149, 768)
now-36,all-27,2_16.wav,(32, 768)
now-36,all-30,2_4.wav,(149, 768)
now-36,all-33,2_7.wav,(149, 768)
all-feature-done
2024-08-20 14:26:30 | INFO | main | ['infer/modules/train/extract/extract_f0_rmvpe.py', '2', '0', '0', 'C:\rvc\RVC1006Nvidia/logs/fx', 'True']
todo-f0-18
todo-f0-18
f0ing,now-0,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_1.wav
f0ing,now-0,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_0.wav
f0ing,now-3,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_4.wav
f0ing,now-3,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_5.wav
f0ing,now-6,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_1.wav
f0ing,now-6,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_11.wav
f0ing,now-9,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_6.wav
f0ing,now-12,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_12.wav
f0ing,now-9,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_7.wav
f0ing,now-15,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_4.wav
f0ing,now-12,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_13.wav
f0ing,now-15,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_5.wav
['infer/modules/train/extract_feature_print.py', 'cuda:0', '1', '0', '0', 'C:\rvc\RVC1006Nvidia/logs/fx', 'v2']
C:\rvc\RVC1006Nvidia/logs/fx
load model(s) from assets/hubert/hubert_base.pt
move model to cuda
all-feature-36
now-36,all-0,0_0.wav,(149, 768)
now-36,all-3,0_11.wav,(67, 768)
now-36,all-6,0_4.wav,(149, 768)
now-36,all-9,0_7.wav,(149, 768)
now-36,all-12,1_1.wav,(149, 768)
now-36,all-15,1_3.wav,(149, 768)
now-36,all-18,1_6.wav,(149, 768)
now-36,all-21,1_9.wav,(149, 768)
now-36,all-24,2_12.wav,(149, 768)
now-36,all-27,2_16.wav,(32, 768)
now-36,all-30,2_4.wav,(149, 768)
now-36,all-33,2_7.wav,(149, 768)
all-feature-done

2024-08-20 14:28:10 | INFO | main | "runtime\python.exe" infer/modules/train/preprocess.py "D:\shuchuyuansheng" 40000 8 "C:\rvc\RVC1006Nvidia/logs/fx" False 3.0
['infer/modules/train/preprocess.py', 'D:\shuchuyuansheng', '40000', '8', 'C:\rvc\RVC1006Nvidia/logs/fx', 'False', '3.0']
start preprocess
['infer/modules/train/preprocess.py', 'D:\shuchuyuansheng', '40000', '8', 'C:\rvc\RVC1006Nvidia/logs/fx', 'False', '3.0']
['C:\rvc\RVC1006Nvidia\infer\modules\train\preprocess.py', 'D:\shuchuyuansheng', '40000', '8', 'C:\rvc\RVC1006Nvidia/logs/fx', 'False', '3.0']
['C:\rvc\RVC1006Nvidia\infer\modules\train\preprocess.py', 'D:\shuchuyuansheng', '40000', '8', 'C:\rvc\RVC1006Nvidia/logs/fx', 'False', '3.0']
['C:\rvc\RVC1006Nvidia\infer\modules\train\preprocess.py', 'D:\shuchuyuansheng', '40000', '8', 'C:\rvc\RVC1006Nvidia/logs/fx', 'False', '3.0']
['C:\rvc\RVC1006Nvidia\infer\modules\train\preprocess.py', 'D:\shuchuyuansheng', '40000', '8', 'C:\rvc\RVC1006Nvidia/logs/fx', 'False', '3.0']
['C:\rvc\RVC1006Nvidia\infer\modules\train\preprocess.py', 'D:\shuchuyuansheng', '40000', '8', 'C:\rvc\RVC1006Nvidia/logs/fx', 'False', '3.0']
['C:\rvc\RVC1006Nvidia\infer\modules\train\preprocess.py', 'D:\shuchuyuansheng', '40000', '8', 'C:\rvc\RVC1006Nvidia/logs/fx', 'False', '3.0']
['C:\rvc\RVC1006Nvidia\infer\modules\train\preprocess.py', 'D:\shuchuyuansheng', '40000', '8', 'C:\rvc\RVC1006Nvidia/logs/fx', 'False', '3.0']
['C:\rvc\RVC1006Nvidia\infer\modules\train\preprocess.py', 'D:\shuchuyuansheng', '40000', '8', 'C:\rvc\RVC1006Nvidia/logs/fx', 'False', '3.0']
D:\shuchuyuansheng/1_lfjq7-njb28-001_(Vocals).wav->Suc.
D:\shuchuyuansheng/fx.wav->Suc.
D:\shuchuyuansheng/jiebudiaoni.wav->Suc.
end preprocess
2024-08-20 14:28:15 | INFO | main | start preprocess
['infer/modules/train/preprocess.py', 'D:\shuchuyuansheng', '40000', '8', 'C:\rvc\RVC1006Nvidia/logs/fx', 'False', '3.0']
D:\shuchuyuansheng/1_lfjq7-njb28-001_(Vocals).wav->Suc.
D:\shuchuyuansheng/fx.wav->Suc.
D:\shuchuyuansheng/jiebudiaoni.wav->Suc.
end preprocess

2024-08-20 14:28:15 | INFO | main | "runtime\python.exe" infer/modules/train/extract/extract_f0_rmvpe.py 2 0 0 "C:\rvc\RVC1006Nvidia/logs/fx" True
2024-08-20 14:28:15 | INFO | main | "runtime\python.exe" infer/modules/train/extract/extract_f0_rmvpe.py 2 1 0 "C:\rvc\RVC1006Nvidia/logs/fx" True
['infer/modules/train/extract/extract_f0_rmvpe.py', '2', '1', '0', 'C:\rvc\RVC1006Nvidia/logs/fx', 'True']
todo-f0-18
f0ing,now-0,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_1.wav
f0ing,now-3,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_5.wav
f0ing,now-6,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_11.wav
f0ing,now-9,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_7.wav
f0ing,now-12,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_13.wav
f0ing,now-15,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_5.wav
['infer/modules/train/extract/extract_f0_rmvpe.py', '2', '0', '0', 'C:\rvc\RVC1006Nvidia/logs/fx', 'True']
todo-f0-18
f0ing,now-0,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_0.wav
f0ing,now-3,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_4.wav
f0ing,now-6,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_1.wav
f0ing,now-9,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_6.wav
f0ing,now-12,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_12.wav
f0ing,now-15,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_4.wav
2024-08-20 14:28:17 | INFO | main | ['infer/modules/train/extract/extract_f0_rmvpe.py', '2', '1', '0', 'C:\rvc\RVC1006Nvidia/logs/fx', 'True']
todo-f0-18
f0ing,now-0,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_1.wav
f0ing,now-3,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_5.wav
f0ing,now-6,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_11.wav
f0ing,now-9,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_7.wav
f0ing,now-12,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_13.wav
f0ing,now-15,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_5.wav
['infer/modules/train/extract/extract_f0_rmvpe.py', '2', '0', '0', 'C:\rvc\RVC1006Nvidia/logs/fx', 'True']
todo-f0-18
f0ing,now-0,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_0.wav
f0ing,now-3,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_4.wav
f0ing,now-6,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_1.wav
f0ing,now-9,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_6.wav
f0ing,now-12,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_12.wav
f0ing,now-15,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_4.wav

2024-08-20 14:28:17 | INFO | main | "runtime\python.exe" infer/modules/train/extract_feature_print.py cuda:0 1 0 0 "C:\rvc\RVC1006Nvidia/logs/fx" v2
['infer/modules/train/extract_feature_print.py', 'cuda:0', '1', '0', '0', 'C:\rvc\RVC1006Nvidia/logs/fx', 'v2']
C:\rvc\RVC1006Nvidia/logs/fx
load model(s) from assets/hubert/hubert_base.pt
move model to cuda
all-feature-36
all-feature-done
2024-08-20 14:28:21 | INFO | main | ['infer/modules/train/extract/extract_f0_rmvpe.py', '2', '1', '0', 'C:\rvc\RVC1006Nvidia/logs/fx', 'True']
todo-f0-18
f0ing,now-0,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_1.wav
f0ing,now-3,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_5.wav
f0ing,now-6,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_11.wav
f0ing,now-9,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_7.wav
f0ing,now-12,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_13.wav
f0ing,now-15,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_5.wav
['infer/modules/train/extract/extract_f0_rmvpe.py', '2', '0', '0', 'C:\rvc\RVC1006Nvidia/logs/fx', 'True']
todo-f0-18
f0ing,now-0,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_0.wav
f0ing,now-3,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/0_4.wav
f0ing,now-6,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_1.wav
f0ing,now-9,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/1_6.wav
f0ing,now-12,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_12.wav
f0ing,now-15,all-18,-C:\rvc\RVC1006Nvidia/logs/fx/1_16k_wavs/2_4.wav
['infer/modules/train/extract_feature_print.py', 'cuda:0', '1', '0', '0', 'C:\rvc\RVC1006Nvidia/logs/fx', 'v2']
C:\rvc\RVC1006Nvidia/logs/fx
load model(s) from assets/hubert/hubert_base.pt
move model to cuda
all-feature-36
all-feature-done

2024-08-20 14:28:21 | INFO | main | Use gpus: 0
2024-08-20 14:28:21 | INFO | main | "runtime\python.exe" infer/modules/train/train.py -e "fx" -sr 40k -f0 1 -bs 4 -g 0 -te 20 -se 5 -pg assets/pretrained_v2/f0G40k.pth -pd assets/pretrained_v2/f0D40k.pth -l 0 -c 0 -sw 0 -v v2
INFO:fx:{'data': {'filter_length': 2048, 'hop_length': 400, 'max_wav_value': 32768.0, 'mel_fmax': None, 'mel_fmin': 0.0, 'n_mel_channels': 125, 'sampling_rate': 40000, 'win_length': 2048, 'training_files': './logs\fx/filelist.txt'}, 'model': {'filter_channels': 768, 'gin_channels': 256, 'hidden_channels': 192, 'inter_channels': 192, 'kernel_size': 3, 'n_heads': 2, 'n_layers': 6, 'p_dropout': 0, 'resblock': '1', 'resblock_dilation_sizes': [[1, 3, 5], [1, 3, 5], [1, 3, 5]], 'resblock_kernel_sizes': [3, 7, 11], 'spk_embed_dim': 109, 'upsample_initial_channel': 512, 'upsample_kernel_sizes': [16, 16, 4, 4], 'upsample_rates': [10, 10, 2, 2], 'use_spectral_norm': False}, 'train': {'batch_size': 4, 'betas': [0.8, 0.99], 'c_kl': 1.0, 'c_mel': 45, 'epochs': 20000, 'eps': 1e-09, 'fp16_run': True, 'init_lr_ratio': 1, 'learning_rate': 0.0001, 'log_interval': 200, 'lr_decay': 0.999875, 'seed': 1234, 'segment_size': 12800, 'warmup_epochs': 0}, 'model_dir': './logs\fx', 'experiment_dir': './logs\fx', 'save_every_epoch': 5, 'name': 'fx', 'total_epoch': 20, 'pretrainG': 'assets/pretrained_v2/f0G40k.pth', 'pretrainD': 'assets/pretrained_v2/f0D40k.pth', 'version': 'v2', 'gpus': '0', 'sample_rate': '40k', 'if_f0': 1, 'if_latest': 0, 'save_every_weights': '0', 'if_cache_data_in_gpu': 0}
INFO:torch.distributed.distributed_c10d:Added key: store_based_barrier_key:1 to store for rank: 0
INFO:torch.distributed.distributed_c10d:Rank 0: Completed store-based barrier for key:store_based_barrier_key:1 with 1 nodes.
DEBUG:infer.lib.infer_pack.models:gin_channels: 256, self.spk_embed_dim: 109
INFO:fx:loaded pretrained assets/pretrained_v2/f0G40k.pth
INFO:fx:
INFO:fx:loaded pretrained assets/pretrained_v2/f0D40k.pth
INFO:fx:
C:\rvc\RVC1006Nvidia\runtime\lib\site-packages\torch\functional.py:641: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error.
Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\native\SpectralOps.cpp:867.)
return _VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore[attr-defined]
C:\rvc\RVC1006Nvidia\runtime\lib\site-packages\torch\functional.py:641: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error.
Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\native\SpectralOps.cpp:867.)
return _VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore[attr-defined]
C:\rvc\RVC1006Nvidia\runtime\lib\site-packages\torch\functional.py:641: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error.
Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\native\SpectralOps.cpp:867.)
return _VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore[attr-defined]
C:\rvc\RVC1006Nvidia\runtime\lib\site-packages\torch\functional.py:641: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error.
Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\native\SpectralOps.cpp:867.)
return _VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore[attr-defined]
C:\rvc\RVC1006Nvidia\runtime\lib\site-packages\torch\functional.py:641: UserWarning: stft with return_complex=False is deprecated. In a future pytorch release, stft will return complex tensors for all inputs, and return_complex=False will raise an error.
Note: you can still call torch.view_as_real on the complex output to recover the old return format. (Triggered internally at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\aten\src\ATen\native\SpectralOps.cpp:867.)
return VF.stft(input, n_fft, hop_length, win_length, window, # type: ignore[attr-defined]
INFO:torch.nn.parallel.distributed:Reducer buckets have been rebuilt in this iteration.
C:\rvc\RVC1006Nvidia\runtime\lib\site-packages\torch\autograd_init.py:200: UserWarning: Grad strides do not match bucket view strides. This may indicate grad was not created according to the gradient layout contract, or that the param's strides changed since DDP was constructed. This is not an error, but may impair performance.
grad.sizes() = [64, 1, 4], strides() = [4, 1, 1]
bucket_view.sizes() = [64, 1, 4], strides() = [4, 4, 1] (Triggered internally at C:\actions-runner_work\pytorch\pytorch\builder\windows\pytorch\torch\csrc\distributed\c10d\reducer.cpp:337.)
Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
INFO:fx:Train Epoch: 1 [0%]
INFO:fx:[0, 0.0001]
INFO:fx:loss_disc=3.620, loss_gen=3.102, loss_fm=11.731,loss_mel=29.830, loss_kl=9.000
DEBUG:matplotlib:matplotlib data path: C:\rvc\RVC1006Nvidia\runtime\lib\site-packages\matplotlib\mpl-data
DEBUG:matplotlib:CONFIGDIR=C:\Users\Administrator.matplotlib
DEBUG:matplotlib:interactive is False
DEBUG:matplotlib:platform is win32
INFO:torch.nn.parallel.distributed:Reducer buckets have been rebuilt in this iteration.
Process Process-1:
Traceback (most recent call last):
File "multiprocessing\process.py", line 315, in bootstrap
File "multiprocessing\process.py", line 108, in run
File "C:\rvc\RVC1006Nvidia\infer\modules\train\train.py", line 271, in run
train_and_evaluate(
File "C:\rvc\RVC1006Nvidia\infer\modules\train\train.py", line 499, in train_and_evaluate
scaler.scale(loss_gen_all).backward()
File "C:\rvc\RVC1006Nvidia\runtime\lib\site-packages\torch_tensor.py", line 487, in backward
torch.autograd.backward(
File "C:\rvc\RVC1006Nvidia\runtime\lib\site-packages\torch\autograd_init.py", line 200, in backward
Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
RuntimeError: CUDA error: out of memory
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.

Start with the reported command in infer-web.py and follow the training steps through infer/modules/train/preprocess.py, infer/modules/train/extract/extract_f0_rmvpe.py, and infer/modules/train/extract_feature_print.py. The log shows repeated preprocessing and feature-extraction output, but it does not identify an error or expected result. First determine which behavior the reporter considers incorrect and what successful completion should look like.