Hi team,
I am using tensorflow version 2.15.0 on my linux machine x86_64 having CUDA 11.5 version and python 3.9.13 for CNN model training purpose whose backbone is Resnet. I successfully trained the model and got the expected result on unseen data while inferencing.
Now i want to deploy the model on jetson nano developer kit aarch64 which is using jetpack 4.6.5 and cudart10.2 where i successfully installed tensorflow version 2.3.1 and python version 3.6.
The problem is tensorflow version mismatch and archietecture diiference.
To overcome this which is the best way .
Follow below things i tried so far
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tried to have same tensorflow version on jetson nano i.e 2.15.0 but it won’t ssupport.
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tried to convert model to tflite format which is achieved and also i did the changes as per that but didn’t succeed
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tried to convert model to tensorrt format on my training machine using ONNX but that is not working .
From the above ways which one is more feasible, please let me know and
Is there any thing i am missing if yes please let me know .