From cbc872a28b4ba55b84ef2e1dc30d74ec9e922006 Mon Sep 17 00:00:00 2001 From: ChasonJiang <1440499136@qq.com> Date: Mon, 21 Apr 2025 23:12:44 +0800 Subject: [PATCH] fix bug --- GPT_SoVITS/TTS_infer_pack/TTS.py | 16 ++++++++-------- 1 file changed, 8 insertions(+), 8 deletions(-) diff --git a/GPT_SoVITS/TTS_infer_pack/TTS.py b/GPT_SoVITS/TTS_infer_pack/TTS.py index f4a225b5..c3d516d8 100644 --- a/GPT_SoVITS/TTS_infer_pack/TTS.py +++ b/GPT_SoVITS/TTS_infer_pack/TTS.py @@ -656,8 +656,8 @@ class TTS: self.bert_model = self.bert_model.half() if self.cnhuhbert_model is not None: self.cnhuhbert_model = self.cnhuhbert_model.half() - if self.bigvgan_model is not None: - self.bigvgan_model = self.bigvgan_model.half() + if self.vocoder is not None: + self.vocoder = self.vocoder.half() else: if self.t2s_model is not None: self.t2s_model = self.t2s_model.float() @@ -667,8 +667,8 @@ class TTS: self.bert_model = self.bert_model.float() if self.cnhuhbert_model is not None: self.cnhuhbert_model = self.cnhuhbert_model.float() - if self.bigvgan_model is not None: - self.bigvgan_model = self.bigvgan_model.float() + if self.vocoder is not None: + self.vocoder = self.vocoder.float() def set_device(self, device: torch.device, save: bool = True): """ @@ -687,8 +687,8 @@ class TTS: self.bert_model = self.bert_model.to(device) if self.cnhuhbert_model is not None: self.cnhuhbert_model = self.cnhuhbert_model.to(device) - if self.bigvgan_model is not None: - self.bigvgan_model = self.bigvgan_model.to(device) + if self.vocoder is not None: + self.vocoder = self.vocoder.to(device) if self.sr_model is not None: self.sr_model = self.sr_model.to(device) @@ -1358,7 +1358,7 @@ class TTS: return sr, audio - def useing_vocoder_synthesis( + def using_vocoder_synthesis( self, semantic_tokens: torch.Tensor, phones: torch.Tensor, speed: float = 1.0, sample_steps: int = 32 ): prompt_semantic_tokens = self.prompt_cache["prompt_semantic"].unsqueeze(0).unsqueeze(0).to(self.configs.device) @@ -1420,7 +1420,7 @@ class TTS: return audio - def useing_vocoder_synthesis_batched_infer( + def using_vocoder_synthesis_batched_infer( self, idx_list: List[int], semantic_tokens_list: List[torch.Tensor],