Tflite runtime inovke error

Technical Support
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1

My Python program is crashing at interpreter.invoke(). I’ve installed all the required packages, executed the necessary .sh setup scripts, and confirmed that the NPU delegate is loading properly. The interpreter.allocate_tensors() function executes without any issues. I’ve also tried using different quantized models, but the program still crashes at interpreter.invoke() without displaying any error message.

2

Hi, I’m the Toradex AI Assistant.

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Hello! Thank you for your detailed explanation of the issue.

Given your steps so far and the silent crash at interpreter.invoke(), let me suggest the main points to check to help resolve the problem:

  1. Set Required Environment Variables
    Ensure you set the following environment variables in your Docker setup (compose file or Dockerfile):
environment:
  - USE_HW_ACCELERATED_INFERENCE=1
  - USE_GPU_INFERENCE=0
  - ACCEPT_FSL_EULA=1

Reference

  1. Delegate Path
    Make sure the delegate is loaded with the exact path:
delegate = load_delegate('/usr/lib/libvx_delegate.so')

Reference

  1. Device Access in Docker
    Add the following to your docker-compose.yml for device access:
device_cgroup_rules:
  - 'c 4:* rmw'
  - 'c 13:* rmw'
  - 'c 199:* rmw'
  - 'c 226:* rmw'
  - 'c 81:* rmw'

Reference

  1. Model Input Format
    Check if your models expect input in RGB format, as required by the NPU integration. A mismatch can cause a crash during inference.
    Reference

  2. Script Completion
    Double-check that your setup scripts ran fully. If you SSH into your container/device, ensure all expected files and configurations are present and scripts finished without error.

  3. Try Known Working Example
    To rule out model compatibility, try running inference with a known working model provided by Toradex or a minimal quantized TFLite example.

  4. Logs and Debugging
    Since nothing is output by your Python program, try running with increased verbosity or checking dmesg and system logs for clues about a possible hardware exception or permissions issue.

If you review these key areas, particularly environment variables, device cgroup rules, and model input format, you’ll often identify the root of silent crashes at interpreter.invoke().

For more details, you can refer to the related Community thread.

Best regards,
Toradex AI Assistant.

3

Hi @vishal

You can find the sample code for python tflite runtime here.

4

Hi allan,
Thank you for your suggestion. I was able to identify the issue based on a response from Toradex AI—it turned out that some environment variables were missing in the Docker Compose file. After adding them, my TensorFlow Lite program is now successfully running on the NPU.

Best regards ,
Vishal