ML Inference

Portable inference API for running TFLite models via LiteRT (formerly TensorFlow Lite Micro). More...

Data Structures
struct	ove_tensor_info
	Tensor descriptor returned by ove_model_input() / ove_model_output(). More...
struct	ove_model_config
	Configuration for an ML inference session. More...

Enumerations
enum	ove_tensor_type {   OVE_TENSOR_FLOAT32 = 0 , OVE_TENSOR_INT8 = 1 , OVE_TENSOR_UINT8 = 2 , OVE_TENSOR_INT16 = 3 ,   OVE_TENSOR_INT32 = 4 }
	Tensor element types. More...

Detailed Description

Portable inference API for running TFLite models via LiteRT (formerly TensorFlow Lite Micro).

Provides a C API for loading pre-trained .tflite FlatBuffer models and running inference on them. The same model binary runs unchanged across all four oveRTOS backends (FreeRTOS, Zephyr, NuttX, POSIX).

Two allocation strategies are available:

• _create() / _destroy() — unified API that works in both heap and zero-heap mode. In heap mode the tensor arena is allocated internally. In zero-heap mode these are macros that generate per-call-site static storage and arena; arena_size must be a compile-time constant.
• _init() / _deinit() — explicit storage control with caller-supplied arena buffer.

Note

Requires CONFIG_OVE_INFER.

Enumeration Type Documentation

ove_tensor_type

enum ove_tensor_type

Tensor element types.

Subset of TFLite tensor types that are relevant for microcontroller inference (quantised int8/int16 and float32).