tensorflow-gpu 2.2 与 CUDA 10.2 一起使用，但需要 cuDNN 7.6.4，它在 NVIDIA 存档中没有 CUDA 10.2 的下载文件答案

【问题标题】：tensorflow-gpu 2.2 works with CUDA 10.2 but requires cuDNN 7.6.4 which doesn't have a download file in NVIDIA archive for CUDA 10.2tensorflow-gpu 2.2 与 CUDA 10.2 一起使用，但需要 cuDNN 7.6.4，它在 NVIDIA 存档中没有 CUDA 10.2 的下载文件
【发布时间】：2021-06-11 03:48:16
【问题描述】：

错误如下，完整日志可以在这里找到：https://pastebin.com/raw/0WQw8ktB

2021-06-10 22:03:04.201770: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcublas.so.10 2021-06-10 22:03:04.420481: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudnn.so.7 2021-06-10 22:03:05.034154: E tensorflow/stream_executor/cuda/cuda_dnn.cc:319] Loaded runtime CuDNN library: 7.4.2 but source was compiled with:
7.6.4.  CuDNN library major and minor version needs to match or have higher minor version in case of CuDNN 7.0 or later version. If using a binary install, upgrade your CuDNN library.  If building from sources, make sure the library loaded at runtime is compatible with the version specified during compile configuration. 2021-06-10 22:03:05.038684: E tensorflow/stream_executor/cuda/cuda_dnn.cc:319] Loaded runtime CuDNN library: 7.4.2 but source was compiled with: 7.6.4.  CuDNN library major and minor version needs to match or have higher minor version in case of CuDNN 7.0 or later version. If using a binary install, upgrade your CuDNN library.  If building from sources, make sure the library loaded at runtime is compatible with the version specified during compile configuration.

这些是我从 nvidia 存档中看到的：

https://developer.nvidia.com/rdp/cudnn-archive

Download cuDNN v7.6.4 (September 27, 2019), for CUDA 10.1
Download cuDNN v7.6.4 (September 27, 2019), for CUDA 10.0
Download cuDNN v7.6.4 (September 27, 2019), for CUDA 9.2
Download cuDNN v7.6.4 (September 27, 2019), for CUDA 9.0

正如您所见，CUDA 10.2 没有 cuDNN，但是我需要在框架的其余部分使用 CUDA 10.2。 tensorflow-gpu 2.2 适用于 CUDA 10.2 但我收到此错误，这意味着我需要使用 cuDNN 7.6.4 而不是 7.4.2

python -c "import tensorflow as tf; print(tf.version.GIT_VERSION, tf.version.VERSION)"
v2.2.0-rc4-8-g2b96f3662b 2.2.0

GPU 型号和内存：

GeForce 1080 Ti (2x) 每个 12GB 内存

$ stat /usr/local/cuda
  File: ‘/usr/local/cuda’ -> ‘/usr/local/cuda-10.2’
  Size: 20          Blocks: 0          IO Block: 4096   symbolic link
Device: fd00h/64768d    Inode: 67157410    Links: 1
Access: (0777/lrwxrwxrwx)  Uid: (    0/    root)   Gid: (    0/    root)
Context: unconfined_u:object_r:usr_t:s0
Access: 2021-06-10 22:12:20.673080083 -0400
Modify: 2020-09-21 09:39:18.559883390 -0400
Change: 2020-09-21 09:39:18.559883390 -0400
 Birth: -

和

[GCC 7.3.1 20180303 (Red Hat 7.3.1-5)] on linux

和

Python 3.8.5 (default, Mar 31 2021, 02:37:07)

tensorflow-gpu 2.2 是使用 pip 安装的。和

$ lsb_release -a
LSB Version:    :core-4.1-amd64:core-4.1-noarch
Distributor ID: CentOS
Description:    CentOS Linux release 7.9.2009 (Core)
Release:    7.9.2009
Codename:   Core

我也看到了这个here，但我找不到下载文件：

【问题讨论】：

标签： python tensorflow centos cudnn

【解决方案1】：

从 NVIDIA 官网下载cudnn-10.2-linux-x64-v7.6.5.32.tgz 后，使用这些命令为CUDA 10.2 安装cuDNN 7.6.5：

$ sudo cp cuda/include/cudnn*.h /usr/local/cuda/include 

$ sudo cp -P cuda/lib64/libcudnn* /usr/local/cuda/lib64 

$ sudo chmod a+r /usr/local/cuda/include/cudnn*.h /usr/local/cuda/lib64/libcudnn*

然后：

$ export LD_LIBRARY_PATH=/usr/local/cuda-10.2/lib64:$LD_LIBRARY_PATH

【讨论】：