Help me ~~ RuntimeError: device-side assert triggered

[ZLeopard]

/opt/conda/conda-bld/pytorch_1524584710464/work/aten/src/THC/THCTensorScatterGather.cu:97: void THCudaTensor_gatherKernel(TensorInfo<Real, IndexType>, TensorInfo<Real, IndexType>, TensorInfo<long, IndexType>, int, IndexType) [with IndexType = unsigned int, Real = float, Dims = 2]: block: [315,0,0], thread: [200,0,0] Assertion indexValue >= 0 && indexValue < src.sizes[dim] failed.
/opt/conda/conda-bld/pytorch_1524584710464/work/aten/src/THC/THCTensorScatterGather.cu:97: void THCudaTensor_gatherKernel(TensorInfo<Real, IndexType>, TensorInfo<Real, IndexType>, TensorInfo<long, IndexType>, int, IndexType) [with IndexType = unsigned int, Real = float, Dims = 2]: block: [315,0,0], thread: [219,0,0] Assertion indexValue >= 0 && indexValue < src.sizes[dim] failed.
/opt/conda/conda-bld/pytorch_1524584710464/work/aten/src/THC/THCTensorScatterGather.cu:97: void THCudaTensor_gatherKernel(TensorInfo<Real, IndexType>, TensorInfo<Real, IndexType>, TensorInfo<long, IndexType>, int, IndexType) [with IndexType = unsigned int, Real = float, Dims = 2]: block: [262,0,0], thread: [117,0,0] Assertion indexValue >= 0 && indexValue < src.sizes[dim] failed.
Traceback (most recent call last):
File "/home/t1070/TeddyZhang/DEEP_LEARNING/faceboxes-master/trainvisdom.py", line 116, in
train()
File "/home/t1070/TeddyZhang/DEEP_LEARNING/faceboxes-master/trainvisdom.py", line 73, in train
loss = criterion(loc_preds,loc_targets,conf_preds,conf_targets)
File "/home/t1070/anaconda2/envs/TeddyZhang/lib/python3.6/site-packages/torch/nn/modules/module.py", line 491, in call
result = self.forward(input, **kwargs)
File "/home/t1070/TeddyZhang/DEEP_LEARNING/faceboxes-master/multibox_loss.py", line 64, in forward
neg = self.hard_negative_mining(conf_loss, pos) # (1621824, (16,21824))
File "/home/t1070/TeddyZhang/DEEP_LEARNING/faceboxes-master/multibox_loss.py", line 29, in hard_negative_mining
conf_loss[pos.view(-1,1)] = 0 #去掉正样本,the rest are neg conf_loss
RuntimeError: device-side assert triggered

[sjiajia]

How do you solve this problem? thank you very much.