FRDM i.MX93 and NXP eIQ Model Zoo compatibility

goytin — Thu, 19 Jun 2025 09:56:14 GMT

Hi.

Is it possible in principle to evaluate NXP eIQ Model Zoo ResNet50 on an FRDM i.MX93 board?
I see that as per NXP eIQ® Model Zoo supported platforms, i.MX93 in general is supported,
but is FRDM i.MX93 supported?

I try to evaluate NXP eIQ Model Zoo ResNet50 performance on an FRDM i.MX93.
I use the FRDM i.MX93 with its default settings: eMMC boot and followed
NXP eIQ Model Zoo ResNet50 README which suggests to create TensorFlow Lite models
by running bash recipe.sh.

To only create (not evaluate) models I needed to overcome the following hurdles:

downgrade Python from 3.12 to 3.11 via pyenv: TensorFlow 2.12.0 demands 3.11,
the default image provides 3.12;
cross-compile git: pyenv needs it and the default Yocto-based image lacks it;
create an additional partition on the eMMC: model creation process easily overflows entire root partition with "No space left on device" (this implies boot from SD, gptfdisk compilation and MBR to GPT conversion);
move eiq-model-zoo repository to this additional partition, create tensorflow_datasets symlink in the home directory.

And all this in vain as I still hit a wall with the kernel OOM Killer.
I can't even create TensorFlow Lite models on the FRDM i.MX93, not to mention test its performance.

Any help on the matter will be appreciated.

i.MX ProcessorsのトピックFRDM i.MX93 and NXP eIQ Model Zoo compatibility

FRDM i.MX93 and NXP eIQ Model Zoo compatibility