def METHOD_NAME(features, filters, bias, indice_pairs, indice_pair_num,
                      num_activate_out, inverse, subm):
    if features.dtype == torch.half or filters.dtypes == torch.float32:
        func = ext_module.fused_indice_conv_forward
    else:
        raise NotImplementedError
    return func(features, filters, bias, indice_pairs, indice_pair_num,
                num_activate_out, int(inverse), int(subm))