mirror of
https://github.com/FunAudioLLM/CosyVoice.git
synced 2026-02-04 09:29:25 +08:00
fix bug
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@@ -99,7 +99,7 @@ def main():
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'prompt_speech_feat': speech_feat, 'prompt_speech_feat_len': speech_feat_len,
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'llm_embedding': utt_embedding, 'flow_embedding': utt_embedding}
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tts_speeches = []
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for model_output in model.inference(**model_input):
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for model_output in model.tts(**model_input):
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tts_speeches.append(model_output['tts_speech'])
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tts_speeches = torch.concat(tts_speeches, dim=1)
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tts_key = '{}_{}'.format(utts[0], tts_index[0])
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@@ -56,14 +56,14 @@ class CosyVoiceModel:
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self.hift_cache_dict = {}
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def load(self, llm_model, flow_model, hift_model):
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self.llm.load_state_dict(torch.load(llm_model, map_location=self.device))
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self.llm.load_state_dict(torch.load(llm_model, map_location=self.device), strict=False)
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self.llm.to(self.device).eval()
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if self.fp16 is True:
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self.llm.half()
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self.flow.load_state_dict(torch.load(flow_model, map_location=self.device))
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self.flow.load_state_dict(torch.load(flow_model, map_location=self.device), strict=False)
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self.flow.to(self.device).eval()
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# in case hift_model is a hifigan model
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hift_state_dict = {k.replace('generator.', ''): v for k, v in torch.load(hift_model, map_location=self.device)}
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hift_state_dict = {k.replace('generator.', ''): v for k, v in torch.load(hift_model, map_location=self.device).items()}
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self.hift.load_state_dict(hift_state_dict, strict=False)
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self.hift.to(self.device).eval()
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