下载匹配cuda的kaldi镜像

Ubuntu 20.04 including Python 3.8 NVIDIA CUDA 11.6.0 cuBLAS 11.8.1.74 NVIDIA cuDNN 8.3.2.44 NVIDIA NCCL 2.11.4 (optimized for NVLink™) rdma-core 36.0 NVIDIA HPC-X 2.10 OpenMPI 4.1.2rc4+ OpenUCX 1.12.0 GDRCopy 2.3 Nsight Systems 2021.5.2.53 TensorRT 8.2.2 SHARP 2.5 DALI 1.9

下载命令：docker pull nvcr.io/nvidia/kaldi:22.01-py3 找包的过程，可以参考之前docker的那篇文章。

docker run --gpus ‘“device=all”’ -itd -v /home/work/wang:/home/work/wang -v /opt/wfs1/aivoice:/opt/wfs1/aivoice –net host –name wyr_tf_cuda11.6 –shm-size=8g nvcr.io/nvidia/kaldi:22.01-py3 bash

配置pip 和 conda vim ~/.pip/pip.conf 添加如下内容

[global] index-url = https://pypi.tuna.tsinghua.edu.cn/simple [install] trusted-host=mirrors.aliyun.com

配置conda镜像

vim ~/.condarc

channels:

- defaults

show_channel_urls: true

default_channels:

- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main

- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/r

- https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/msys2

custom_channels:

conda-forge: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud

msys2: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud

bioconda: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud

menpo: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud

pytorch: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud

simpleitk: https://mirrors.tuna.tsinghua.edu.cn/anaconda/cloud

安装tensorflow-gpu==1.14.0

第一次尝试：

pip install tensorflow-gpu==1.14.0 -i https://pypi.tuna.tsinghua.edu.cn/simple

找不到版本。原因是自己的python是3.8。

tensorflow1.14需要python3.7版本，而python3.8版本对应的是tensorflow2版本。

于是首先创建python3.7环境。

conda create -n audio python=3.7

conda activate audio

第二次尝试：

pip install tensorflow-gpu==1.14.0 -i https://pypi.tuna.tsinghua.edu.cn/simple

安装成功。但是import出错。

错误1: TypeError: Descriptors cannot not be created directly. If this call came from a _pb2.py file, your generated code is out of date and must be regenerated with protoc >= 3.19.0. If you cannot immediately regenerate your protos, some other possible workarounds are:

Downgrade the protobuf package to 3.20.x or lower.Set PROTOCOL_BUFFERS_PYTHON_IMPLEMENTATION=python (but this will use pure-Python parsing and will be much slower).

解决方法： pip install protobuf==3.19.0

错误2: /home/work/wangyaru05/anaconda3/envs/audio/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:516: FutureWarning: Passing (type, 1) or ‘1type’ as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / ‘(1,)type’. _np_qint8 = np.dtype([(“qint8”, np.int8, 1)]) /home/work/wangyaru05/anaconda3/envs/audio/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:517: FutureWarning: Passing (type, 1) or ‘1type’ as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / ‘(1,)type’. _np_quint8 = np.dtype([(“quint8”, np.uint8, 1)]) /home/work/wangyaru05/anaconda3/envs/audio/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:518: FutureWarning: Passing (type, 1) or ‘1type’ as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / ‘(1,)type’. _np_qint16 = np.dtype([(“qint16”, np.int16, 1)]) /home/work/wangyaru05/anaconda3/envs/audio/lib/python3.7/site-packages/tensorflow/python/framework/dtypes.py:519: FutureWarning: Passing (type, 1) or ‘1type’ as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / ‘(1,)type’. _np_quint16 = np.dtype([(“quint16”, np.uint16, 1)])

解决方法： pip install numpy==1.16.4

其它包的安装 中间运行项目的时候，发现少一些包，比如resampy，pandas，使用pip单独安装会安装最新版本，然后卸载numpy1.16.4，安装更新版本的，这样会导致tensorflow又会报错，所以需要找到合适的resampy和pandas版本。从网上没找到说明，就手动一直实验，不好弄。后来发现可以用下面的方法解决：

pip install numpy==1.16.4 resampy numba scipy pandas h5py 这样写一块就能限制resampy、numba、scipy的版本，让他们自动兼容

推荐链接

评论可见，请评论后查看内容，谢谢！！！
 您阅读本篇文章共花了：