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chore(format): run black on dev (#1619)

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Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
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github-actions[bot] 2023-12-20 14:47:37 +09:00 committed by GitHub
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commit 0f8a5facd9
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1 changed files with 36 additions and 29 deletions
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17
tools/rvc_for_realtime.py
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@ -62,6 +62,7 @@ class RVC:
"""
try:
if config.dml == True:
def forward_dml(ctx, x, scale):
ctx.scale = scale
res = x.clone().detach()
@ -261,7 +262,7 @@ class RVC:
self.inp_q.put((idx, x[:tail], res_f0, n_cpu, ts))
else:
self.inp_q.put(
(idx, x[part_length * idx - 320: tail], res_f0, n_cpu, ts)
(idx, x[part_length * idx - 320 : tail], res_f0, n_cpu, ts)
)
while 1:
res_ts = self.opt_q.get()
@ -276,7 +277,7 @@ class RVC:
else:
f0 = f0[2:]
f0bak[
part_length * idx // 160: part_length * idx // 160 + f0.shape[0]
part_length * idx // 160 : part_length * idx // 160 + f0.shape[0]
] = f0
f0bak = signal.medfilt(f0bak, 3)
f0bak *= pow(2, f0_up_key / 12)
@ -328,14 +329,20 @@ class RVC:
def get_f0_fcpe(self, x, f0_up_key):
if hasattr(self, "model_fcpe") == False:
from torchfcpe import spawn_bundled_infer_model
printt("Loading fcpe model")
self.model_fcpe = spawn_bundled_infer_model(self.device)
f0 = self.model_fcpe.infer(
f0 = (
self.model_fcpe.infer(
torch.from_numpy(x).to(self.device).unsqueeze(0).float(),
sr=16000,
decoder_mode='local_argmax',
decoder_mode="local_argmax",
threshold=0.006,
).squeeze().cpu().numpy()
)
.squeeze()
.cpu()
.numpy()
)
f0 *= pow(2, f0_up_key / 12)
return self.get_f0_post(f0)