tensorflow-gpu 2.2 適用於 CUDA 10.2 但需要 cuDNN 7.6.4，它在 NVIDIA 存檔中沒有 CUDA 10.2 的下載文件

Question

錯誤如下，完整的日志可以在這里找到： 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.

這些是我從 nvidia 檔案中看到的：

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

如您所見，CUDA 10.2 沒有 cuDNN，但是，我需要為我的框架的 rest 使用 CUDA 10.2。 tensorflow-gpu 2.2 適用於 CUDA 10.2 但我收到此錯誤，這意味着我需要使用 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 model 和 memory：

GeForce 1080 Ti (2x) 每個 12GB memory

$ 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 安裝的。 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

我也在這里看到了這個，但我找不到下載文件：

Answer 1

從 NVIDIA 官方網站下載cudnn-10.2-linux-x64-v7.6.5.32.tgz后，使用這些命令為CUDA 10.2安裝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*

接着：

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