@Samuel-Lehman This is an issue with TensorFlow and your model. You could try enabling the v2 control flow ops as mentioned here (https://www.tensorflow.org/api_docs/python/tf/compat/v1/enable_control_flow_v2). Your model likely contains some older ops that are not compatible with Tflite (you mentioned having trained it a few years back). You could try the official solution given by tensorflow as linked or you could perhaps retrain your model with newer libraries.

Note that you do not necessarily need to train with TensorFlow; you can train using any other framework as well. Moreover, you are converting a frozen graph, and the official docs recommend converting from a saved model (https://ai.google.dev/edge/litert/models/convert_tf). Hope this resolves your issues!

@Samuel-Lehman I think the issue is with the tflite version running on voxl, which does not support v3 ops. An update to tflite on the voxl is being pushed but it will take some time to be merged into the main SDK. However, you can try tensorflow 2.17.1 from this branch.

Note that since it is not completely integrable, running it is slightly more complex. Make sure you are using the newest voxl-cross image to build voxl-tflite-server.

On Voxl, it cannot run directly, and you would have to run it via a Docker container. You can find a sample Dockerfile provided in docker_samples/ in the 'update_tf' branch. For further context on integrating opencl please refer to this.

Hopefully, the updated tflite will contain the necessary v3 op and it works smoothly.

@Samuel-Lehman I think the issue is with the tflite version running on voxl, which does not support v3 ops. An update to tflite on the voxl is being pushed but it will take some time to be merged into the main SDK. However, you can try tensorflow 2.17.1 from this branch.

Note that since it is not completely integrable, running it is slightly more complex. Make sure you are using the newest voxl-cross image to build voxl-tflite-server.

On Voxl, it cannot run directly, and you would have to run it via a Docker container. You can find a sample Dockerfile provided in docker_samples/ in the 'update_tf' branch. For further context on integrating opencl please refer to this.

Hopefully, the updated tflite will contain the necessary v3 op and it works smoothly.

@Samuel-Lehman This is an issue with TensorFlow and your model. You could try enabling the v2 control flow ops as mentioned here (https://www.tensorflow.org/api_docs/python/tf/compat/v1/enable_control_flow_v2). Your model likely contains some older ops that are not compatible with Tflite (you mentioned having trained it a few years back). You could try the official solution given by tensorflow as linked or you could perhaps retrain your model with newer libraries.

Note that you do not necessarily need to train with TensorFlow; you can train using any other framework as well. Moreover, you are converting a frozen graph, and the official docs recommend converting from a saved model (https://ai.google.dev/edge/litert/models/convert_tf). Hope this resolves your issues!