NVIDIA updated their machine learning repos

[omen23]

fix wrong version numbers - libcudnn is still working with old numbers but libnvinfer5 is not
you can also use 7.6.0.64-1+cuda10.0 for libcudnn7 but it auto upgraded to 7.6.0.64-1+cuda10.1 - so who cares and libnvinfer5 will only install with libnvinfer5=5.1.5-1+cuda10.0 or libnvinfer5=5.1.2-1+cuda10.0 if you pass it the correct version number. Same for the development library. Just signed the CLA
Would be nice if I knew this earlier (using a Ubuntu / kubuntu 19.04 disco base system with repos for LTS 18.04.2)

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[omen23]

I signed it

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[omen23]

newest library version

[omen23]

hey i know you are busy but this is important information for people trying to install TensorRT - it won't work with wrong version numbrs of libnvinfer5

[tfboyd]

I see a cuDNN specific for CUDA 10 (I suspect same binary or similar) in the downloads. I did not check the repo; could you check again. I realized it is not upgrading to CUDA 10.1 but it would avoid any visual confusion if it was just CUDA 10.0. I am adding lambda who can verify what version of TensorRT we should be suggesting. We also will want to upgrade our docker images. I have been wanting to stay on cuDNN 7.5; but if we need to move forward for TensorRT then that is a valid reason.

[tfboyd]

@aaroey

• Is this the TensorRT we need and do we need to upgrade to cuDNN 7.6? I think we spoke about this but I forgot.

Docs team, you may (not passive aggressive honestly asking) want to change some permissions because I could not add lambda to review this. Not sure if that is desired; it was a bit of a road block/speed bump.

[lamberta]

@tfboyd I think github requires write access to the repo to assign reviewers. I'm happy to give that to you, but it's not something we want to set for everyone because not everyone understands the copybara sync workflow. the github permission model is not very flexible :/

Maybe @gunan knows better?

[gunan]

I think we can also add collaborators to the repo and assign as reviewers?

[lamberta]

@gunan @tfboyd Yes, we have a number of collaborator teams already attached to this repo. I can assign folks in these teams, but I have write access to this repo.

[lamberta]

I should note: even with write access, I can not assign users that are not in these collaborator teams

[gunan]

Just checked repo permissions.
You are right, editing pull requests requires "Write" permissions to the repository.

[omen23]

sudo apt-get install --no-install-recommends \
        cuda-10-0 \
        libcudnn7=7.6.0.64-1+cuda10.0  \
        libcudnn7-dev=7.4.1.5-1+cuda10.0

works too its the same file - I explained it in my original post

you can also use 7.6.0.64-1+cuda10.0 for libcudnn7 but it (apt) auto upgraded to 7.6.0.64-1+cuda10.1

I fixed the libcudnn version of the library to use the 10.0 one
Atleast if the version numbers for TensorRT are not updated the manual is broken.

Regards

[aaroey]

@tfboyd yes 7.5.1 is the TensorRT version we'd like to use but we need to remove the installation of nvinfer-runtime-trt-repo-ubuntu1804-5.0.2-ga-cuda10.0. Just commented.

[tfboyd]

Check if we need to install the nvinfer-runti-trt-repo.... Then we are done and this is a nice improvement.

[tfboyd]

Ok, last item. We need to test if the install of the libnvinfra can be done without needing to install the nvinfer-runti-trt-repo. I suspect Yes given the code below is install a version different than the repo; but I would like that validated. Easy to do if you have a local fresh ubuntu docker or VM. I may get to it but I suspect anyone would be faster than me.

[omen23]

Hey,
libnvinfer5 and libnvinfer-dev are actually in the repo http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64
which gets added earlier in the instalaltion process!

• so we actually don't need the nvinfer-runtime-trt-repo-ubuntu1804-5.0.2-ga-cuda10.0 repository.

Regards

PS: I think everything is fixed now – optically and logically .. so lets put it on the site so new users can install TensorRT… and the new versions of libcudnn7

[omen23]

$ apt-cache policy libnvinfer-dev
libnvinfer-dev:
  Installed: 5.1.5-1+cuda10.0
  Candidate: 5.1.5-1+cuda10.1
  Version table:
     5.1.5-1+cuda10.1 500
        500 http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64  Packages
 *** 5.1.5-1+cuda10.0 500
        500 http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64  Packages
        100 /var/lib/dpkg/status
     5.1.2-1+cuda10.1 500
        500 http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64  Packages
     5.1.2-1+cuda10.0 500
        500 http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64  Packages

$ sudo apt-get install libnvinfer-dev=5.1.5-1+cuda10.0 --reinstall
Reading package lists... Done
Building dependency tree       
Reading state information... Done
The following package was automatically installed and is no longer required:
  libnvidia-common-418
Use 'sudo apt autoremove' to remove it.
0 upgraded, 0 newly installed, 1 reinstalled, 0 to remove and 8 not upgraded.
Need to get 44,3 MB of archives.
After this operation, 0 B of additional disk space will be used.
Get:1 http://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64  libnvinfer-dev 5.1.5-1+cuda10.0 [44,3 MB]
Fetched 44,3 MB in 4s (12,3 MB/s)         
(Reading database ... 322083 files and directories currently installed.)
Preparing to unpack .../libnvinfer-dev_5.1.5-1+cuda10.0_amd64.deb ...
Unpacking libnvinfer-dev (5.1.5-1+cuda10.0) over (5.1.5-1+cuda10.0) ...
Setting up libnvinfer-dev (5.1.5-1+cuda10.0) ...

[omen23]

ironed out everything – ready to be pushed on the manual website

[aaroey]

Approve for TensorRT related changes, thanks!
Please wait for other approvals before merging.

[tfboyd]

@omen23 Thank you for doing all the hardwork. Testing this stuff takes time, I would know for sure, and I really appreciate it. LGTM from me.

[tfboyd]

LGTM

[lamberta]

Thanks, everyone. Appreciate it!