add cosyvoice3 vllm example

This commit is contained in:
lyuxiang.lx
2025-12-08 10:55:53 +00:00
parent bfa835a74b
commit b4dd67a8af
3 changed files with 29 additions and 10 deletions

View File

@@ -88,6 +88,7 @@ def convert_onnx_to_trt(trt_model, trt_kwargs, onnx_model, fp16):
logging.info("Succesfully convert onnx to trt...")
# NOTE do not support bistream inference as only speech token embedding/head is kept
def export_cosyvoice2_vllm(model, model_path, device):
if os.path.exists(model_path):
return
@@ -98,12 +99,14 @@ def export_cosyvoice2_vllm(model, model_path, device):
dtype = torch.bfloat16
# lm_head
new_lm_head = torch.nn.Linear(in_features=feature_size, out_features=pad_vocab_size, bias=True)
use_bias = True if model.llm_decoder.bias is not None else False
new_lm_head = torch.nn.Linear(in_features=feature_size, out_features=pad_vocab_size, bias=use_bias)
with torch.no_grad():
new_lm_head.weight[:vocab_size] = model.llm_decoder.weight
new_lm_head.bias[:vocab_size] = model.llm_decoder.bias
new_lm_head.weight[vocab_size:] = 0
new_lm_head.bias[vocab_size:] = 0
if use_bias is True:
new_lm_head.bias[:vocab_size] = model.llm_decoder.bias
new_lm_head.bias[vocab_size:] = 0
model.llm.model.lm_head = new_lm_head
new_codec_embed = torch.nn.Linear(in_features=feature_size, out_features=pad_vocab_size)
# embed_tokens
@@ -121,9 +124,12 @@ def export_cosyvoice2_vllm(model, model_path, device):
del model.llm.model.config.eos_token_id
model.llm.model.config.vocab_size = pad_vocab_size
model.llm.model.config.tie_word_embeddings = False
model.llm.model.config.use_bias = True
model.llm.model.config.use_bias = use_bias
model.llm.model.save_pretrained(model_path)
os.system('sed -i s@Qwen2ForCausalLM@CosyVoice2ForCausalLM@g {}/config.json'.format(os.path.abspath(model_path)))
if use_bias is True:
os.system('sed -i s@Qwen2ForCausalLM@CosyVoice2ForCausalLM@g {}/config.json'.format(os.path.abspath(model_path)))
else:
os.system('sed -i s@Qwen2ForCausalLM@Qwen2ForCausalLM@g {}/config.json'.format(os.path.abspath(model_path)))
model.llm.model.config.vocab_size = tmp_vocab_size
model.llm.model.config.tie_word_embeddings = tmp_tie_embedding
model.llm.model.set_input_embeddings(embed_tokens)

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@@ -88,7 +88,7 @@ def cosyvoice3_example():
torchaudio.save('hotfix_{}.wav'.format(i), j['tts_speech'], cosyvoice.sample_rate)
def main():
# cosyvoice_example()
cosyvoice_example()
cosyvoice2_example()
cosyvoice3_example()

View File

@@ -4,20 +4,33 @@ from vllm import ModelRegistry
from cosyvoice.vllm.cosyvoice2 import CosyVoice2ForCausalLM
ModelRegistry.register_model("CosyVoice2ForCausalLM", CosyVoice2ForCausalLM)
from cosyvoice.cli.cosyvoice import CosyVoice2
from cosyvoice.utils.file_utils import load_wav
from cosyvoice.cli.cosyvoice import CosyVoice2, CosyVoice3
from cosyvoice.utils.common import set_all_random_seed
from tqdm import tqdm
def main():
def cosyvoice2_example():
""" CosyVoice2 vllm usage
"""
cosyvoice = CosyVoice2('pretrained_models/CosyVoice2-0.5B', load_jit=True, load_trt=True, load_vllm=True, fp16=True)
for i in tqdm(range(100)):
set_all_random_seed(i)
for _, _ in enumerate(cosyvoice.inference_zero_shot('收到好友从远方寄来的生日礼物,那份意外的惊喜与深深的祝福让我心中充满了甜蜜的快乐,笑容如花儿般绽放。', '希望你以后能够做的比我还好呦。', './asset/zero_shot_prompt.wav', stream=False)):
continue
def cosyvoice3_example():
""" CosyVoice3 vllm usage
"""
cosyvoice = CosyVoice3('pretrained_models/CosyVoice3-0.5B', load_jit=True, load_trt=True, load_vllm=True, fp16=True)
prompt_speech_16k = load_wav('./asset/zero_shot_prompt.wav', 16000)
for i in tqdm(range(100)):
set_all_random_seed(i)
for _, _ in enumerate(cosyvoice.inference_zero_shot('收到好友从远方寄来的生日礼物,那份意外的惊喜与深深的祝福让我心中充满了甜蜜的快乐,笑容如花儿般绽放。', '希望你以后能够做的比我还好呦。', prompt_speech_16k, stream=False)):
for _, _ in enumerate(cosyvoice.inference_zero_shot('收到好友从远方寄来的生日礼物,那份意外的惊喜与深深的祝福让我心中充满了甜蜜的快乐,笑容如花儿般绽放。', '希望你以后能够做的比我还好呦。', './asset/zero_shot_prompt.wav', stream=False)):
continue
def main():
cosyvoice2_example()
cosyvoice3_example()
if __name__ == '__main__':
main()