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https://github.com/FunAudioLLM/CosyVoice.git
synced 2026-02-04 17:39:25 +08:00
add func inference_bistream_vllm
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@@ -104,13 +104,23 @@ class CosyVoiceModel:
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with self.llm_context:
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if isinstance(text, Generator):
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assert isinstance(self, CosyVoice2Model), 'streaming input text is only implemented for CosyVoice2!'
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for i in self.llm.inference_bistream(text=text,
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prompt_text=prompt_text.to(self.device),
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prompt_text_len=torch.tensor([prompt_text.shape[1]], dtype=torch.int32).to(self.device),
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prompt_speech_token=llm_prompt_speech_token.to(self.device),
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prompt_speech_token_len=torch.tensor([llm_prompt_speech_token.shape[1]], dtype=torch.int32).to(self.device),
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embedding=llm_embedding.to(self.device)):
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self.tts_speech_token_dict[uuid].append(i)
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if self.vllm_codec_engine is None:
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for i in self.llm.inference_bistream(text=text,
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prompt_text=prompt_text.to(self.device),
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prompt_text_len=torch.tensor([prompt_text.shape[1]], dtype=torch.int32).to(self.device),
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prompt_speech_token=llm_prompt_speech_token.to(self.device),
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prompt_speech_token_len=torch.tensor([llm_prompt_speech_token.shape[1]], dtype=torch.int32).to(self.device),
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embedding=llm_embedding.to(self.device)):
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self.tts_speech_token_dict[uuid].append(i)
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else:
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for i in self.llm.inference_bistream_vllm(text=text,
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prompt_text=prompt_text.to(self.device),
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prompt_text_len=torch.tensor([prompt_text.shape[1]], dtype=torch.int32).to(self.device),
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prompt_speech_token=llm_prompt_speech_token.to(self.device),
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prompt_speech_token_len=torch.tensor([llm_prompt_speech_token.shape[1]], dtype=torch.int32).to(self.device),
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embedding=llm_embedding.to(self.device),
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vllm_codec_engine=self.vllm_codec_engine):
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self.tts_speech_token_dict[uuid].append(i)
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else:
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for i in self.llm.inference(text=text.to(self.device),
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text_len=torch.tensor([text.shape[1]], dtype=torch.int32).to(self.device),
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