TensorFlow中的cudnn编译配置

Question

Ubuntu 14.04，CUDA版本7.5.18，每晚构建的Tensorflow

tf.nn.max_pool()在tensorflow中运行操作时，出现以下错误：

[tensorflow / stream_executor / cuda / cuda_dnn.cc：286]已加载的cudnn库：5005，但是源代码是针对4007编译的。如果使用二进制安装，请升级您的cudnn库以使其匹配。如果从源构建，请确保加载的库与您在编译配置期间指定的版本匹配。

W tensorflow / stream_executor / stream.cc：577]尝试使用不具有DNN支持的StreamExecutor执行DNN操作

追溯（最近一次通话）：

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如何在tensorflow的编译配置中指定我的cudnn版本？

Answer 1

进入TensorFlow源码目录，然后执行配置文件：/.configure.

以下是TensorFlow 文档中的示例：

$ ./configure
Please specify the location of python. [Default is /usr/bin/python]:
Do you wish to build TensorFlow with GPU support? [y/N] y
GPU support will be enabled for TensorFlow

Please specify which gcc nvcc should use as the host compiler. [Default is
/usr/bin/gcc]: /usr/bin/gcc-4.9

Please specify the Cuda SDK version you want to use, e.g. 7.0. [Leave
empty to use system default]: 7.5

Please specify the location where CUDA 7.5 toolkit is installed. Refer to
README.md for more details. [default is: /usr/local/cuda]: /usr/local/cuda

Please specify the Cudnn version you want to use. [Leave empty to use system
default]: 4.0.4

Please specify the location where the cuDNN 4.0.4 library is installed. Refer to
README.md for more details. [default is: /usr/local/cuda]: /usr/local/cudnn-r4-rc/

Please specify a list of comma-separated Cuda compute capabilities you want to
build with. You can find the compute capability of your device at:
https://developer.nvidia.com/cuda-gpus.
Please note that each additional compute capability significantly increases your
build time and binary size. [Default is: \"3.5,5.2\"]: 3.5

Setting up Cuda include
Setting up Cuda lib64
Setting up Cuda bin
Setting up Cuda nvvm
Setting up CUPTI include
Setting up CUPTI lib64
Configuration finished