def METHOD_NAME(rpn_results_list, batch_gt_instances):
    """Create sample results that can be passed to Head.get_targets."""
    num_imgs = len(rpn_results_list)
    feat = torch.rand(1, 1, 3, 3)
    assign_config = dict(
        type='MaxIoUAssigner',
        pos_iou_thr=0.5,
        neg_iou_thr=0.5,
        min_pos_iou=0.5,
        ignore_iof_thr=-1)
    sampler_config = dict(
        type='CombinedSampler',
        num=4,
        pos_fraction=0.5,
        neg_pos_ub=3,
        add_gt_as_proposals=True,
        pos_sampler=dict(type='InstanceBalancedPosSampler'),
        neg_sampler=dict(type='RandomSampler'))
    bbox_assigner = TASK_UTILS.build(assign_config)
    bbox_sampler = TASK_UTILS.build(sampler_config)
    sampling_results = []
    for i in range(num_imgs):
        assign_result = bbox_assigner.assign(rpn_results_list[i],
                                             batch_gt_instances[i])
        sampling_result = bbox_sampler.sample(
            assign_result,
            rpn_results_list[i],
            batch_gt_instances[i],
            feats=feat)
        sampling_results.append(sampling_result)
    return sampling_results