A Fundamental End-to-End Speech Recognition Toolkit and Open Source SOTA Pretrained Models, Supporting Speech Recognition, Voice Activity Detection, Text Post-processing etc.
What is your question?
我用进程方式启动AutoModel处理,16K单声道的wav音频数据,vad模型内部处理数据直接卡住不动,请大佬帮我看看进程启动下vad模型内部处理数据为什么会卡住。
funasr->utils->load_utils.py的64行 data_or_path_or_list = data_or_path_or_list.mean(0)
ps:用线程模式就能正常执行,但咱们线程模式长时间运行,有严重的内存泄漏,而且vad不支持多线程。
Code
.....
pool = multiprocessing.Pool(2)
pool.apply(func=convert, args=(wavepath))
)
What have you tried?
In a pytorch docker container, run pip install funasr and then the script above.
What's your environment?
OS (e.g., Linux):
FunASR Version (e.g., 1.0.0): 1.0.19
ModelScope Version (e.g., 1.11.0): None (do not need it)
PyTorch Version (e.g., 2.0.0): 2.2.2
How you installed funasr (pip, source): pip
Python version: 3.10.14
GPU (e.g., V100M32): NVIDIA GeForce RTX 4090
CUDA/cuDNN version (e.g., cuda11.7): cuda11.8
Docker version (e.g., funasr-runtime-sdk-cpu-0.4.1): pytorch/pytorch:2.2.2-cuda11.8-cudnn8-runtime
Any other relevant information:
What is your question? 我用进程方式启动AutoModel处理,16K单声道的wav音频数据,vad模型内部处理数据直接卡住不动,请大佬帮我看看进程启动下vad模型内部处理数据为什么会卡住。 funasr->utils->load_utils.py的64行 data_or_path_or_list = data_or_path_or_list.mean(0)
Code ..... pool = multiprocessing.Pool(2) pool.apply(func=convert, args=(wavepath))
..... def convert(wavepath): model = AutoModel(model="iic/speech_paraformer-large-vad-punc_asr_nat-zh-cn-16k-common-vocab8404-pytorch", model_revision="v2.0.4", vad_model="iic/speech_fsmn_vad_zh-cn-16k-common-pytorch", vad_model_revision="v2.0.4", punc_model="iic/punc_ct-transformer_zh-cn-common-vocab272727-pytorch", punc_model_revision="v2.0.4", spk_model="iic/speech_campplus_sv_zh-cn_16k-common", spk_model_revision="v2.0.2", ncpu=1, device="cpu", disable_pbar=True, disable_log=False )
) What have you tried? In a pytorch docker container, run pip install funasr and then the script above.
What's your environment? OS (e.g., Linux): FunASR Version (e.g., 1.0.0): 1.0.19 ModelScope Version (e.g., 1.11.0): None (do not need it) PyTorch Version (e.g., 2.0.0): 2.2.2 How you installed funasr (pip, source): pip Python version: 3.10.14 GPU (e.g., V100M32): NVIDIA GeForce RTX 4090 CUDA/cuDNN version (e.g., cuda11.7): cuda11.8 Docker version (e.g., funasr-runtime-sdk-cpu-0.4.1): pytorch/pytorch:2.2.2-cuda11.8-cudnn8-runtime Any other relevant information: