Unable to test on a very small dataset (ValueError: need at least one array to concatenate)

[CharviVitthal]

Hello,
I want to test on a very small dataset.
I reduced my validation dataset size to only 3 point clouds. (The same issue is also present if dataset contains only 1 or 2 point clouds). The folder has the required structure - labels, images, calib, velodyne, velodyne reduced. create_data.py works fine. But test.py gives the following error. When I increase my data size, everything works fine again.
Traceback (most recent call last):
File "test.py", line 209, in
main()
File "test.py", line 204, in main
result = get_official_eval_result(gt_annos, outputs, current_classes=class_names)
File "/home/charvi/SA-SSD/mmdet/core/evaluation/kitti_eval.py", line 839, in get_official_eval_result
gt_annos, dt_annos, current_classes, min_overlaps, compute_aos, difficultys)
File "/home/charvi/SA-SSD/mmdet/core/evaluation/kitti_eval.py", line 708, in do_eval_v2
min_overlaps, compute_aos)
File "/home/charvi/SA-SSD/mmdet/core/evaluation/kitti_eval.py", line 586, in eval_class_v3
rets = calculate_iou_partly(dt_annos, gt_annos, metric, num_parts)
File "/home/charvi/SA-SSD/mmdet/core/evaluation/kitti_eval.py", line 376, in calculate_iou_partly
gt_boxes = np.concatenate([a["bbox"] for a in gt_annos_part], 0)
File "<array_function internals>", line 6, in concatenate
ValueError: need at least one array to concatenate

Any help is appreciated.
(In line 376 "gt_boxes = np.concatenate([a["bbox"] for a in gt_annos_part], 0)" gt_annos_part is coming an empty array)

Best regards,
Charvi