run tensorflow on Jetson TX2 with GPU out wrong result

On TX2, I have installed Jetpack3.3 and Tensorflow 1.9.0 use:
pip3 install --extra-index-url=https://developer.download.nvidia.com/compute/redist/jp33 tensorflow-gpu

run graph on CPU make right result but run on GPU make wrong result and out different results with same input
example code: https://1drv.ms/u/s!AhFk3ICqlZI2irJdcWsWHKtBHhrt5w

run on CPU: CUDA_VISIBLE_DEVICES=’’ python3 test.py
run on GPU: python3 test.py

what error?

Hi,

Do you meet any error when executing?
Or the application can finish successfully but with the incorrect results?

We will check your sample and update more information with you later.
Thanks

no error when executing
only have notify: ARM64 does not support NUMA - returning NUMA node zero
the application finish successfully with the incorrect results

I tried build tensorflow C++ on TX2 follow: https://github.com/JasonAtNvidia/JetsonTFBuild, but same error

this is text file define graph: https://1drv.ms/u/s!AhFk3ICqlZI2irJeV3K_0KyvMB8mcw

Exactly the same problem occurred in my environment. (TX2, Jetpack3.3, Tensorflow 1.9.0, my task is object ditection with SSD, too).
Further, I tryed to run the same program on a windows PC with GeForce, I got right result.

Hi,

This is a known issue. TensorFlow may introduce incorrect result with SpaceToBatchND.
You can check this topic for information:
https://devtalk.nvidia.com/default/topic/1037898

This issue is fixed in the Xavier platform.
We test your sample on Xavier and can get the identical result with CPU and GPU.

CPU

[[[ 74.377      320.73145    139.79294    377.59125      0.99432826
     1.        ]
  [  1.4652786  299.86053     71.74264    367.73016      0.9911488
     1.        ]
  [119.930405     0.9353714  265.55936    113.78609      0.96522236
     1.        ]
  [ 67.6715     183.38559    200.57294    264.9446       0.9565499
     1.        ]
  [187.84546    174.78589    271.09146    259.42136      0.9555303
     1.        ]
  [  3.7699127  210.44226     66.127335   268.4802       0.94328606
     1.        ]]]

GPU

[[[ 74.37714    320.73148    139.79294    377.59125      0.99432814
     1.        ]
  [  1.4652481  299.86063     71.74257    367.7301       0.9911486
     1.        ]
  [119.930435     0.9353714  265.5593     113.786095     0.9652203
     1.        ]
  [ 67.67179    183.38574    200.57285    264.94446      0.95654756
     1.        ]
  [187.84558    174.78603    271.0915     259.4213       0.9555299
     1.        ]
  [  3.7699547  210.44241     66.12728    268.48013      0.94328594
     1.        ]]]

Thanks.