def METHOD_NAME(model: NNCFNetwork) -> Dict[str, np.ndarray]:
    output = {}
    quantization_types = [class_type.__name__ for class_type in QUANTIZATION_MODULES.registry_dict.values()]
    nncf_module_quantizations = get_all_modules_by_type(model, quantization_types)
    # This is not general logic, just used for the particular test
    nncf_module_quantizations.update(
        {str(scope): module[0] for scope, module in model.nncf.get_tracing_context()._post_hooks.items()}
    )
    for name, nncf_module_quantization in nncf_module_quantizations.items():
        input_low, input_high = nncf_module_quantization.get_input_low_input_high()
        input_low = input_low.cpu().detach().numpy()
        input_high = input_high.cpu().detach().numpy()
        output[str(name)] = {"input_low": input_low, "input_high": input_high}
    return output