cudnn compile configuration in TensorFlow
Ubuntu 14.04, CUDA Version 7.5.18, nightly build of tensorflow
While running a tf.nn.max_pool() operation in tensorflow, I got the following error:
E tensorflow/stream_executor/cuda/cuda_dnn.cc:286] Loaded cudnn library: 5005 but source was compiled against 4007. If using a binary install, upgrade your cudnn library to match. If building from sources, make sure the library loaded matches the version you specified during compile configuration.
W tensorflow/stream_executor/stream.cc:577] attempting to perform DNN operation using StreamExecutor without DNN support
Traceback (most recent call last):
...
How do I specify my cudnn version in the compile configuration of tensorflow?
Answer
Go in the directory of TensorFlow source code, then execute the configuration file: /.configure.
Here is an example from the TensorFlow documentation:
$ ./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