fumiama/Retrieval-based-Voice-Conversion-WebUI
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fix(dml): train extract_f0_print error

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ModuleNotFoundError: No module named 'torch.privateuseone' due to new prosess
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源文雨
2025-11-21 16:52:17 +08:00
parent 7fa122045f
commit 43d19eb00e
13 changed files with 50 additions and 39 deletions
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9
rvc/layers/nsf.py
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@@ -1,4 +1,4 @@
from typing import Optional, List
from typing import Optional, List, Union
import math
import torch
@@ -83,7 +83,7 @@ class NSFGenerator(torch.nn.Module):
self.conv_pre = Conv1d(
initial_channel, upsample_initial_channel, 7, 1, padding=3
)
resblock = ResBlock1 if resblock == "1" else ResBlock2
resblockcls = ResBlock1 if resblock == "1" else ResBlock2
self.ups = nn.ModuleList()
for i, (u, k) in enumerate(zip(upsample_rates, upsample_kernel_sizes)):
@@ -114,12 +114,13 @@ class NSFGenerator(torch.nn.Module):
self.noise_convs.append(Conv1d(1, c_cur, kernel_size=1))
self.resblocks = nn.ModuleList()
ch = 0
for i in range(len(self.ups)):
ch: int = upsample_initial_channel // (2 ** (i + 1))
ch = upsample_initial_channel // (2 ** (i + 1))
for j, (k, d) in enumerate(
zip(resblock_kernel_sizes, resblock_dilation_sizes)
):
self.resblocks.append(resblock(ch, k, d))
self.resblocks.append(resblockcls(ch, k, d))
self.conv_post = Conv1d(ch, 1, 7, 1, padding=3, bias=False)
self.ups.apply(call_weight_data_normal_if_Conv)