I have a Jetson AGX Xavier with jetpack 4.6.1, the pre installed cuda with this jetpack is 10.2
I want now to install tensorflow from source.
The required TF for my occasion according to this documentation is TF ==2.7.0 +nv22.01
But as you can see TF=2.7 needs cuda 11.2
I tried to install manually TF=2.3.0 but i get this message:
“ERROR: Could not find a version that satisfies the requirement tensorflow==2.3.0+nv20.9 (from versions: 1.15.5+nv22.1, 2.7.0+nv22.1)
ERROR: No matching distribution found for tensorflow==2.3.0+nv20.9”
Is it necessary to downgrade Jetpack or to upgrade my cuda version.
By upgrading cuda may this arise any problem?
Is there any other solution?
You can install v2.7.0+nv22.1 on JetPack 4.6.1 directly.
The compatibility is solved and tested by our internal team.
Of course, the first thing I did was to install TF v2.7 but when I run my module, I get this message :
“2022-06-07 15:28:06.214347: W tensorflow/stream_executor/gpu/asm_compiler.cc:111] ** WARNING ** You are using ptxas 10.2.300, which is older than 11.1. ptxas before 11.1 is known to miscompile XLA code, leading to incorrect results or invalid-address errors.”
It’s obvious a warning msg about the compatibility between Cuda and TF
So I try to figure out a solution among all those warnings
Could you share a simple reproducible script for the error?
We test the TF package on a Xavier board and it can run correctly.
Python 3.6.9 (default, Mar 15 2022, 13:55:28)
[GCC 8.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
2022-06-13 15:41:00.615857: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1019] ARM64 does not support NUMA - returning NUMA node zero
2022-06-13 15:41:00.736515: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1019] ARM64 does not support NUMA - returning NUMA node zero
2022-06-13 15:41:00.737156: I tensorflow/stream_executor/cuda/cuda_gpu_executor.cc:1019] ARM64 does not support NUMA - returning NUMA node zero
In order to proceed with my work, I downgraded the Jetpack to 4.5.1.
When I finish my task, I will answer again to this topic
Is this still an issue to support? Any result can be shared? Thanks
Hi, no I work now on jetpack 4.5.1 which works fine by my side.
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