您好，我根据你论文中给出的oi数据集处理方式进行处理，会出现问题：

Start training
/opt/conda/conda-bld/pytorch_1670525541035/work/aten/src/ATen/native/cuda/IndexKernel.cu:92: operator(): block: [0,0,0], thread: [4,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds" failed.
/opt/conda/conda-bld/pytorch_1670525541035/work/aten/src/ATen/native/cuda/IndexKernel.cu:92: operator(): block: [0,0,0], thread: [5,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds" failed.
/opt/conda/conda-bld/pytorch_1670525541035/work/aten/src/ATen/native/cuda/IndexKernel.cu:92: operator(): block: [0,0,0], thread: [6,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds" failed.
/opt/conda/conda-bld/pytorch_1670525541035/work/aten/src/ATen/native/cuda/IndexKernel.cu:92: operator(): block: [0,0,0], thread: [7,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds" failed.
/opt/conda/conda-bld/pytorch_1670525541035/work/aten/src/ATen/native/cuda/IndexKernel.cu:92: operator(): block: [0,0,0], thread: [12,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds" failed.
/opt/conda/conda-bld/pytorch_1670525541035/work/aten/src/ATen/native/cuda/IndexKernel.cu:92: operator(): block: [0,0,0], thread: [13,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds" failed.
/opt/conda/conda-bld/pytorch_1670525541035/work/aten/src/ATen/native/cuda/IndexKernel.cu:92: operator(): block: [0,0,0], thread: [14,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds" failed.
/opt/conda/conda-bld/pytorch_1670525541035/work/aten/src/ATen/native/cuda/IndexKernel.cu:92: operator(): block: [0,0,0], thread: [15,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds" failed.
Traceback (most recent call last):
File "main.py", line 239, in
main(args)
File "main.py", line 191, in main
train_stats = train_one_epoch(model, criterion, data_loader_train, optimizer, device, epoch, args.clip_max_norm)
File "/home/sherry/xfn/RelTR/engine.py", line 40, in train_one_epoch
loss_dict = criterion(outputs, targets)
File "/home/sherry/anaconda3/envs/de_detr/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/home/sherry/xfn/RelTR/models/reltr.py", line 298, in forward
indices = self.matcher(outputs_without_aux, targets)
File "/home/sherry/anaconda3/envs/de_detr/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, **kwargs)
File "/home/sherry/anaconda3/envs/de_detr/lib/python3.7/site-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "/home/sherry/xfn/RelTR/models/matcher.py", line 118, in forward
cost_sub_giou = -generalized_box_iou(box_cxcywh_to_xyxy(sub_bbox), box_cxcywh_to_xyxy(sub_tgt_bbox))
File "/home/sherry/xfn/RelTR/util/box_ops.py", line 50, in generalized_box_iou
assert (boxes1[:, 2:] >= boxes1[:, :2]).all(), boxes1
RuntimeError: CUDA error: device-side assert triggered
CUDA kernel errors might be asynchronously reported at some other API call,so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.

请问是否可以处理后的oi数据集？
期待得到您的回复，非常感谢！