onnx_diagnostic.tasks.object_detection

onnx_diagnostic.tasks.object_detection.get_inputs(model: Module, config: Any | None, input_width: int, input_height: int, input_channels: int, batch_size: int = 2, dynamic_rope: bool = False, add_second_input: bool = False, **kwargs)

Generates inputs for task object-detection.

Parameters:

• model – model to get the missing information

• config – configuration used to generate the model

• batch_size – batch size

• input_channels – input channel

• input_width – input width

• input_height – input height

Returns:

dictionary

onnx_diagnostic.tasks.object_detection.random_input_kwargs(config: Any) → Tuple[Dict[str, Any], Callable]

Inputs kwargs.

If the configuration is None, the function selects typical dimensions.

onnx_diagnostic.tasks.object_detection.reduce_model_config(config: Any) → Dict[str, Any]

Reduces a model size.