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fixed oversight where input audio does not resample (lol...)

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mrq 2024-09-27 20:27:53 -05:00
parent 039482a48e
commit 10df2ef5f3
1 changed files with 3 additions and 2 deletions
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vall_e/emb/qnt.py
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@ -495,7 +495,7 @@ def encode(wav: Tensor, sr: int = cfg.sample_rate, device="cuda", return_metadat
if wav.dim() < 3: if wav.dim() < 3:
wav = wav.unsqueeze(0) wav = wav.unsqueeze(0)
# skip unnecessary resample # skip unnecessary resample
if sr != model.sample_rate and wav.shape[1] != 1: if sr != model.sample_rate or wav.shape[1] != 1:
wav = convert_audio(wav, sr, model.sample_rate, 1) wav = convert_audio(wav, sr, model.sample_rate, 1)
wav = wav.to(device) wav = wav.to(device)
@ -510,8 +510,9 @@ def encode(wav: Tensor, sr: int = cfg.sample_rate, device="cuda", return_metadat
if wav.dim() < 3: if wav.dim() < 3:
wav = wav.unsqueeze(0) wav = wav.unsqueeze(0)
# skip unnecessary resample # skip unnecessary resample
if sr != model.sample_rate and wav.shape[1] != model.channels: if sr != model.sample_rate or wav.shape[1] != model.channels:
wav = convert_audio(wav, sr, model.sample_rate, model.channels) wav = convert_audio(wav, sr, model.sample_rate, model.channels)
wav = wav.to(device) wav = wav.to(device)
with torch.autocast("cuda", dtype=cfg.inference.dtype, enabled=cfg.inference.amp): with torch.autocast("cuda", dtype=cfg.inference.dtype, enabled=cfg.inference.amp):