Hi,
I trained a TF/Keras model (UNet architecture) with a Tesla K40. When I use it with the Jetson Xavier (Jetpack 4.4.1), however, I get very different results, despite I don’t get any error message (the only “strange” message i get is: ‘ARM64 does not support NUMA - returning NUMA node zero’ - but no failure).
Jetson output is very strange - this is an example of the output array (or part of it):
JETSON:
[0.07289112]
[0.10021071]
[0.10021071]
[0.10021071]
[0.10021071]
[0.10021071]
[0.10021071]
[0.10021071]
[0.10021071]
[0.10021071]
[0.10021071]
[0.10021071]
[0.10021071]
[0.10021071]
[0.10021071]
(numbers change after a while, but not so many of them
while on TESLA:
[0.09022264]
[0.08399124]
[0.09759483]
[0.08107567]
[0.07902569]
[0.11560011]
[0.78396565]
[0.81917554]
[0.31143603]
[0.09954672]
[0.31214723]
[0.0928173 ]
[0.07590267]
[0.88202167]
[0.08934084]
Model was trained with TensorFlow 2.3.1 (tried also with TF 2.0)