Mirrors/Retrieval-based-Voice-Conversion-WebUI
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Add DirectML support for PyMSS, support interrupting separation, fix CUDA Graph errors in input/output denoising, and update pip installation dependencies

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This commit is contained in:
RVC-Boss
2026-07-23 22:00:19 +08:00
parent 132126af72
commit 7aa5f1698a
163 changed files with 36697 additions and 3590 deletions
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54
realtime_gui.py
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@@ -675,6 +675,8 @@ if __name__ == "__main__":
).to(self.config.device)
else:
self.resampler2 = None
# Bundled torch.istft is not CUDA Graph-capturable, so TorchGate
# stays eager while resampling and RVC inference still use graphs.
self.tg = TorchGate(
sr=self.gui_config.samplerate, n_fft=4 * self.zc, prop_decrease=0.9
).to(self.config.device)
@@ -697,15 +699,7 @@ if __name__ == "__main__":
short = self.input_wav[
-self.sola_buffer_frame - self.block_frame :
].unsqueeze(0)
run_cuda_graph(
self.tg,
"realtime-input-noise-reduction",
lambda short_audio, full_audio: self.tg(
short_audio, full_audio
),
short,
self.input_wav.unsqueeze(0),
)
self.tg(short, self.input_wav.unsqueeze(0))
resample_input = self.input_wav[-self.block_frame - 2 * self.zc :]
run_cuda_graph(
@@ -730,15 +724,7 @@ if __name__ == "__main__":
inferred,
)
if self.gui_config.O_noise_reduce:
run_cuda_graph(
self.tg,
"realtime-output-noise-reduction",
lambda short_audio, full_audio: self.tg(
short_audio, full_audio
),
inferred.unsqueeze(0),
self.output_buffer.unsqueeze(0),
)
self.tg(inferred.unsqueeze(0), self.output_buffer.unsqueeze(0))
torch.cuda.synchronize(self.config.device)
printt(i18n("CUDA Graph预热完成"))
except Exception:
@@ -817,16 +803,12 @@ if __name__ == "__main__":
].clone()
# input noise reduction and resampling
if self.gui_config.I_noise_reduce:
self.input_wav_denoise[: -self.block_frame] = self.input_wav_denoise[
self.block_frame :
].clone()
input_wav = self.input_wav[-self.sola_buffer_frame - self.block_frame :]
input_wav = run_cuda_graph(
self.tg,
"realtime-input-noise-reduction",
lambda short, full: self.tg(short, full),
input_wav.unsqueeze(0),
self.input_wav.unsqueeze(0),
self.input_wav_denoise[: -self.block_frame] = self.input_wav_denoise[
self.block_frame :
].clone()
input_wav = self.input_wav[-self.sola_buffer_frame - self.block_frame :]
input_wav = self.tg(
input_wav.unsqueeze(0), self.input_wav.unsqueeze(0)
).squeeze(0)
input_wav[: self.sola_buffer_frame] *= self.fade_in_window
input_wav[: self.sola_buffer_frame] += (
@@ -875,16 +857,12 @@ if __name__ == "__main__":
infer_wav = self.input_wav[self.extra_frame :].clone()
# output noise reduction
if self.gui_config.O_noise_reduce and self.function == "vc":
self.output_buffer[: -self.block_frame] = self.output_buffer[
self.block_frame :
].clone()
self.output_buffer[-self.block_frame :] = infer_wav[-self.block_frame :]
infer_wav = run_cuda_graph(
self.tg,
"realtime-output-noise-reduction",
lambda short, full: self.tg(short, full),
infer_wav.unsqueeze(0),
self.output_buffer.unsqueeze(0),
self.output_buffer[: -self.block_frame] = self.output_buffer[
self.block_frame :
].clone()
self.output_buffer[-self.block_frame :] = infer_wav[-self.block_frame :]
infer_wav = self.tg(
infer_wav.unsqueeze(0), self.output_buffer.unsqueeze(0)
).squeeze(0)
# volume envelop mixing
if self.gui_config.rms_mix_rate < 1 and self.function == "vc":