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Do we specifically need cuDNN v5.1 (as suggested) for TensorFlow, or would the latest version (v6.0) work as well? Is there backward compatibility in cuDNN versions?

hekimgil
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    The latest version (TensorFlow 1.0.1) did not work with cuDNN v6 for me.(as of April 1). – Ali Apr 02 '17 at 18:21
  • Ah, thank you. Then cuDNN versions are likely not backward compatible and with every new version, we need to wait for any infrastructure to be upgraded/tweaked for the new version... – hekimgil Apr 02 '17 at 18:51

3 Answers3

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No, cuDNN 6.0 is not supported in the latest 1.2 version. But there is a hope: the official release notes tell the following:

TensorFlow 1.2 may be the last time we build with cuDNN 5.1. Starting with TensorFlow 1.3, we will try to build all our prebuilt binaries with cuDNN 6.0. While we will try to keep our source code compatible with cuDNN 5.1, it will be best effort.

So hopefully the next 1.3 version will use cuDNN 6.0. Especially now, when 7.0 is right around the corner.

Salvador Dali
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Today ( 21 August 2017 ) I installed the latest Tensorflow release v1.3 and I can confirm that it REQUIRES cuDNN v6.0 and WILL NOT WORK with v5.1 . It will ask in fact for the library libcudnn.so.6 and not the libcudnn.so.5

P.s. If you want it to work with cuDNN 5.1. you can install a previous version e.g. v1.2 which is at this link:

https://www.tensorflow.org/versions/r0.12/get_started/os_setup#virtualenv_installation

simo23
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This would be an updated answer of Salvador Dali's response.

I have upgraded the tensorflow version to 1.2.1 and then cudnn 6.0 seems to work with no problem. I used pip

pip install tensorflow
pip install --upgrade tensorflow

Installation details are here.

Sumsuddin Shojib
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