I already tried to ask here, but didn't get a satisfying answer. I'll try again in here since I want to use the i.MX RT1170.
I already know that TensorFlow Lite (TFL) supports the Google Edge TPU, for instance through the Coral Dev Board (Linux required).
However I'd like to know whether eIQ/TensorFlow Lite for Microcontrollers (TFLM) is compatible as well.
What I want to do is design a bare-metal (no OS, so no Python etc.) Embedded System with a Cortex-M microcontroller and use the TPU to accelerate an image classifier using TFLM. I'd like to use the TPU either through the standalone chip (Accelerator Module) or the USB Accelerator. They both use USB2.0.
There's a similar system from Google, the Dev Board Micro, which mounts a Cortex-M (i.MX RT1170) and according to the product description "Supports TensorFlow Lite and TensorFlow Lite for Microcontrollers". But unfortunately it's still "coming soon" and I don't find any other useful info or similar projects online. Being an official product I assume TFLM (and as a result, eIQ) should support the Edge TPU but I don't understand whether it's already supported now or maybe it will be in the future only when the Dev Board Micro is released.
I tried to have a look at the GitHub repo of TFLM and at the line 56 I found this but I don't know to how to interpret it:
kTfLiteEdgeTpuContext = 2, // Placeholder for Edge TPU support.
Thank you!
