mirror of
https://github.com/FunAudioLLM/CosyVoice.git
synced 2026-02-05 01:49:25 +08:00
add trt script TODO
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@@ -21,7 +21,7 @@ from cosyvoice.utils.file_utils import logging
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class CosyVoice:
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def __init__(self, model_dir, load_script=True):
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def __init__(self, model_dir, load_jit=True, load_trt=True):
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instruct = True if '-Instruct' in model_dir else False
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self.model_dir = model_dir
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if not os.path.exists(model_dir):
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@@ -39,9 +39,12 @@ class CosyVoice:
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self.model.load('{}/llm.pt'.format(model_dir),
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'{}/flow.pt'.format(model_dir),
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'{}/hift.pt'.format(model_dir))
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if load_script:
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self.model.load_script('{}/llm.text_encoder.fp16.zip'.format(model_dir),
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if load_jit:
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self.model.load_jit('{}/llm.text_encoder.fp16.zip'.format(model_dir),
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'{}/llm.llm.fp16.zip'.format(model_dir))
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if load_trt:
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# TODO
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self.model.load_trt()
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del configs
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def list_avaliable_spks(self):
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@@ -53,12 +53,17 @@ class CosyVoiceModel:
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self.hift.load_state_dict(torch.load(hift_model, map_location=self.device))
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self.hift.to(self.device).eval()
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def load_script(self, llm_text_encoder_model, llm_llm_model):
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def load_jit(self, llm_text_encoder_model, llm_llm_model):
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llm_text_encoder = torch.jit.load(llm_text_encoder_model)
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self.llm.text_encoder = llm_text_encoder
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llm_llm = torch.jit.load(llm_llm_model)
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self.llm.llm = llm_llm
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def load_trt(self):
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# TODO 你需要的TRT推理的准备
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self.flow.decoder.estimator = xxx
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self.flow.decoder.session = xxx
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def llm_job(self, text, text_len, prompt_text, prompt_text_len, llm_prompt_speech_token, llm_prompt_speech_token_len, llm_embedding, this_uuid):
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with self.llm_context:
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for i in self.llm.inference(text=text.to(self.device),
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