ZephyrOS with Updated TFLM

This guide explains how to download and set up ZephyrOS with the latest TFLM (TensorFlow Lite for Microcontrollers) on your system. Follow the steps below:

Downloading ZephyrOS

1. Download Zephyr by following the instructions provided here -- I am working with Zephyr Branch 3.6

2. Once downloaded, run the Blinky example to ensure everything is working correctly.

Downloading the Latest TFLM

1. Install gmake using Homebrew: brew install gmake
2. Clone the TFLM repository: git clone https://www.github.com/tensorflow/tflite-micro.git (you can also delete the already exsisting tflite-micro in zephyr and clone latest tflite-micro in that same zephyr location -- make sure you cmakelists.txt has the correct path for tflite-micro. However, I didnt do that here, I have a seperate folder for tflite-micro) currently I am at commit 9245002844166fc3d0c41917b9b6e1678e8dfad1
3. Navigate to the TFLM directory: cd tflite-micro
4. Build TFLM using the provided Makefile: gmake -f tensorflow/lite/micro/tools/make/Makefile

If you want to build TFLM for the Cortex-M4 processor:

• Build TFLM with the specified target and target architecture: gmake -f tensorflow/lite/micro/tools/make/Makefile TARGET=cortex_m_generic TARGET_ARCH=cortex-m4 third_party_downloads

• gmake -f tensorflow/lite/micro/tools/make/Makefile TARGET=cortex_m_generic TARGET_ARCH=cortex-m4 OPTIMIZED_KERNEL_DIR=cmsis_nn microlite

replace m4 by m33 if you want to build for nrf53

Building and Deploying ZephyrOS with TFLM

1. Copy the hello_world folder from hello_world_1.1 and place it in the following directory: zephyrproject/zephyr/samples/basic.

2. Build the project using the following commands:

   cd ~/zephyrproject
west build -p always -b nrf5340dk_nrf5340_cpuapp zephyr/samples/basic/hello_world/

3. Make sure to edit the path to your latest TFLM in the CMakeLists.txt file and check the target_arch (for nRF5340 or nRF52, it should be cortex-m33 or cortex-m4).

4. Deploy the built project using the following command: west flash

Once the above steps are completed successfully, follow these additional instructions to replace the TFLM image with the latest version:

1. Copy the latest TFLM image and replace the existing one in the following directory: zephyrproject/modules/lib/tflite-micro.

2. Copy the hello_world_1.2 file and place it in the following directory: zephyrproject/zephyr/samples/basic.

3. Build the updated project using the following command: west build -p always -b nrf5340dk_nrf5340_cpuapp zephyr/samples/basic/hello_world_1.2/

4. You may see an error for fixedpoint.h:

• copy fixedpoint folder and detect_platform.h from tflite-micro/tensorflow/lite/micro/tools/make/downloads/gemmlowp/internal and copy it to tflite-micro/tensorflow/lite/kernels/internal
• now open the fixedpoint/fixedpoint.h and change the path of detect_platform.h from ../internal/detect_platform.h to ../detect_platform.h

5. You may see an error for DWT not defined:

• something is wrong witht he gmake, clean the tflite-micro build and repeat the following commands: gmake -f tensorflow/lite/micro/tools/make/Makefile gmake -f tensorflow/lite/micro/tools/make/Makefile TARGET=cortex_m_generic TARGET_ARCH=cortex-m4 third_party_downloads gmake -f tensorflow/lite/micro/tools/make/Makefile TARGET=cortex_m_generic TARGET_ARCH=cortex-m4 OPTIMIZED_KERNEL_DIR=cmsis_nn microlite

6. Make sure to edit the path to your latest TFLM in the CMakeLists.txt file and check the target_arch (for nRF5340 or nRF52, it should be cortex-m4).

7. Deploy the updated project using the following command: west flash

Viewing the Output

To view the output, you can use the picocom tool:

1. Install picocom using Homebrew: brew install picocom
2. Run picocom with the appropriate settings: picocom -fh -b 115200 --imap lfcrlf /dev/tty…

Building TFLM for Cortex-M7

If you want to build TFLM for the Cortex-M7 processor:

1. Navigate to the TFLM directory: cd ~ cd tflite-micro

2. Clean the previous build (if necessary): gmake -f tensorflow/lite/micro/tools/make/Makefile clean

3. Build TFLM with the specified target, target architecture, and CMSIS-NN enabled: gmake -f tensorflow/lite/micro/tools/make/Makefile TARGET=cortex_m_generic OPTIMIZED_KERNEL_DIR=cmsis_nn TARGET_ARCH=cortex-m7 microlite

Note: If using the latest TFLM and building without CMSIS-NN, make sure to comment out the line OPTIMIZED_KERNEL_DIR=cmsis_nn in CMakeLists.txt