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Update infer_v2.py: solve the problem of persistent cache buildup (#382)

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* Update infer_v2.py

clear old cache

* Update infer_v2.py: solve the problem of persistent cache buildup

clear old cache
This commit is contained in:
kj863257rc
2025-09-18 13:59:45 +08:00
committed by GitHub
parent 9e391a920a
commit 64cb31a6c3
1 changed files with 9 additions and 0 deletions
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indextts/infer_v2.py
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@@ -370,6 +370,12 @@ class IndexTTS2:
# 如果参考音频改变了，才需要重新生成, 提升速度
if self.cache_spk_cond is None or self.cache_spk_audio_prompt != spk_audio_prompt:
if self.cache_spk_cond is not None:
self.cache_spk_cond = None
self.cache_s2mel_style = None
self.cache_s2mel_prompt = None
self.cache_mel = None
torch.cuda.empty_cache()
audio,sr = self._load_and_cut_audio(spk_audio_prompt,15,verbose)
audio_22k = torchaudio.transforms.Resample(sr, 22050)(audio)
audio_16k = torchaudio.transforms.Resample(sr, 16000)(audio)
@@ -421,6 +427,9 @@ class IndexTTS2:
emovec_mat = emovec_mat.unsqueeze(0)
if self.cache_emo_cond is None or self.cache_emo_audio_prompt != emo_audio_prompt:
if self.cache_emo_cond is not None:
self.cache_emo_cond = None
torch.cuda.empty_cache()
emo_audio, _ = self._load_and_cut_audio(emo_audio_prompt,15,verbose,sr=16000)
emo_inputs = self.extract_features(emo_audio, sampling_rate=16000, return_tensors="pt")
emo_input_features = emo_inputs["input_features"]