JetPack 3.3 — L4T R28.2.1 Release for Jetson TX1/TX2

We’re pleased to announce that JetPack 3.3 is now available for Jetson TX2/TX2i and Jetson TX1!

The highlight of this release is TensorRT 4.0, enabling support for TensorFlow’s TensorRT integration feature. Also, cuDNN has a small update to support the new TensorRT version, and all other JetPack components remain unchanged from JetPack 3.2.1. Please view the Release Notes.

JetPack 3.3 components:

  • L4T R28.2.1 (TX2/TX2i)
  • L4T R28.2    (TX1)
  • CUDA 9.0
  • cuDNN 7.1.5
  • TensorRT 4.0
  • VisionWorks 1.6

Download JetPack…https://developer.nvidia.com/embedded/jetpack
Release Notes…https://developer.nvidia.com/embedded/jetpack-notes
L4T Release Notes…https://developer.nvidia.com/embedded/dlc/release-notes-r2821
L4T R28.2.1 Page…https://developer.nvidia.com/embedded/linux-tegra
L4T Archive Page…https://developer.nvidia.com/embedded/linux-tegra-archive

I have download JetPack3.3 and find that the TensorRT version is still 3.0 and cuDNN version is still 7.0.5. What wrong?

Did you download JetPack 3.3 to a fresh directory? Which region are you in?

Can you post the .json files from under jetpack_downloads/ that JetPack created? (you can use [ code ] [ /code ] tags (no spaces) to post the contents)

I am in China.
The manifest.json contains:

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Why all the posts from users got deleted? Or I just don’t see it. There was a good question about tensorRT and Python.

BTW, good job Dustin :)

Are these the posts you were looking for?

https://devtalk.nvidia.com/default/topic/1037813/announcements/jetpack-3-3-mdash-l4t-r28-2-1-release-for-jetson-tx1-tx2/

I think this forum software might not have support for linking threads, so there’re multiple duplicated announcement threads are being posted in different sub-forums.

-albertr

Yes Exactly. Thank you very much! very appreciate.

My teammate have downloaded all the packages from American server, the TensorRT version is 4.0.
So I guess the server in China hasn’t been updated yet.

What happend with Russian server? I woudn’t upload new and old Jetpack versions on my dev boards for 2 weeks… always see problem with transfering of CUDA OpenCV and TensorRT pockets!
Massage from terminal:

dpkg-query: package 'cuda-toolkit-9-0' is not installed and no information is available
dpkg-query: package 'libfreeimage-dev' is not installed and no information is available
dpkg-query: package 'libopenmpi-dev' is not installed and no information is available
dpkg-query: package 'openmpi-bin' is not installed and no information is available
Use dpkg --info (= dpkg-deb --info) to examine archive files,
and dpkg --contents (= dpkg-deb --contents) to list their contents.
1
Error: CUDA cannot be installed on device. This may be caused by other apt-get command running on device when installing CUDA. Please use apt-get command in a terminal to make sure following packages are installed correctly on device before continuing:
cuda-toolkit-9-0 libgomp1 libfreeimage-dev libopenmpi-dev openmpi-bin
After these packages are installed on device, press Enter key to continue

I neet install 40 pockets manual and after Jetpack ended the uploading i don’t fimd much of librares. What happend?

It doesn’t look like your manifest contains references to JetPack 3.3. We will check if the geo cache needs flushed in your region.

Does the JetPack 3.3 have Nvidia’s part number

The NVIDIA part numbers for the Jetsons? You can find those here:

https://developer.nvidia.com/embedded/faq#jetson-part-numbers

Hi there is no part number for the JETPACK 3.3 in that link

Software releases do not get part numbers.

There was a CDN caching issue on the mainland China servers which has been resolved now. Please try again and you should be able to access Jetpack 3.3 and it’s contents.

Appreciate for you guys output, it seems like tensorflow for jetpack 4.4/tensorrt 4.0 has not released, when this version will come?

Hi adonishong, we are working on the TF 1.9 pip whl for JetPack 3.3, we will update this thread with it when it’s ready.

Looking forward to it ^_^

Met a new issue last night, we are converting a network(which has PRELU layer included, abs opt is required for PRELU) from uff with giexec, this issues stop us:

UFFParser: Parser error: resnet_v1_50/prelu0/Abs: Unary not supported for other non-constant node

Also tried a script (scripts/convert_plan.py) from official tensorflow to tensorrt python project:
https://github.com/NVIDIA-Jetson/tf_to_trt_image_classification
Still got similar error:

UFFParser: Parser error: resnet_v1_50/prelu0/Abs: Unary not supported for other non-constant node

From tensorrt 4.0 document, abs operation is support for TensorFlow, my question is with this coming TF 1.9 pip whl for JetPack 3.3, will this issue be solved? Seems like this issue comes from “/usr/lib/aarch64-linux-gnu/libnvparsers.so.4.1.3”

OK, please post this issue as a new topic on the TX2 forum so it can be referred to properly. Thanks.