Wanting to run anomaly-based intrusion detection on AGX Xavier

Description

As the title says, I’m trying to implement anomaly-based intrusion detection on the AGX Xavier. I’m using pandas dataframes for training/testing. Its certainly possible without tensorrt, but is incredibly slow using a Keras savedmodel (even running maxn and ./jetson_clocks.sh). I’m finding very little information on the use of TensorRT for intrusion detection or with pandas dataframes. Is it possible? Or is Keras necessary for this particular application?

Environment

TensorRT Version:
GPU Type:
Nvidia Driver Version:
CUDA Version:
CUDNN Version:
Operating System + Version:
Python Version (if applicable):
TensorFlow Version (if applicable):
PyTorch Version (if applicable):
Baremetal or Container (if container which image + tag):

Relevant Files

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Steps To Reproduce

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Hi,
This looks like a Jetson issue. Please refer to the below samlples in case useful.

For any further assistance, we recommend you to raise it to the respective platform from the below link

Thanks!