How rsankar1996/my_tinyml_app works
This is embedded TinyML firmware for running a weather model on a Renesas RA6M4 board. The visible entry point reaches the HAL, while the repository includes a compiled-in TFLite model and TensorFlow Lite Micro runtime components. The main application and HAL implementation were not sampled, so their detailed wiring and the exact input/output interface cannot be confirmed; the graph shows only the supported high-level workflow and runtime layers.
Main entry points: main_application.cpp Weather application · hal_entry.cpp HAL entry · all_ops_resolver.cc Operator resolver · micro_context.cc Tensor context
Components 12
Firmware app
- Firmware entry
e2_studio_project/ra_gen/main.c - HAL entry
e2_studio_project/src/hal_entry.cpp - Weather application
e2_studio_project/src/main_application.cpp
TinyML runtime
- Operator resolver
e2_studio_project/src/tensorflow/lite/micro/all_ops_resolver.cc - Inference kernels
e2_studio_project/src/tensorflow/lite/micro/kernels - Tensor context
e2_studio_project/src/tensorflow/lite/micro/micro_context.cc - Arena allocator
e2_studio_project/src/tensorflow/lite/micro/arena_allocator/simple_memory_allocator.cc
Model data
- Embedded model
e2_studio_project/src/weather_model.cc
Board platform
- Board initialization
e2_studio_project/ra/board/ra6m4_ek/board_init.c - Peripheral services
e2_studio_project/ra/fsp/src/bsp/mcu/all/bsp_common.c
Other components
- Weather input
- Weather result
Connections 10
- Weather input → Weather application: provides input
- Firmware entry → HAL entry: calls
- HAL entry → Weather application: enters
- Weather application → Embedded model: reads model
- Weather application → Operator resolver: configures operators
- Weather application → Tensor context: uses tensor context
- Tensor context → Arena allocator: allocates tensors
- Operator resolver → Inference kernels: registers operators
- Weather application → Weather result: produces result
- Board initialization → Peripheral services: uses services