运行结果及报错内容
C:/w/b/windows/pytorch/aten/src/ATen/native/cuda/Loss.cu:111: block: [61,0,0], thread: [28,0,0] Assertion input_val >= zero && input_val <= one failed.
C:/w/b/windows/pytorch/aten/src/ATen/native/cuda/Loss.cu:111: block: [61,0,0], thread: [29,0,0] Assertion input_val >= zero && input_val <= one failed.
C:/w/b/windows/pytorch/aten/src/ATen/native/cuda/Loss.cu:111: block: [61,0,0], thread: [30,0,0] Assertion input_val >= zero && input_val <= one failed.
C:/w/b/windows/pytorch/aten/src/ATen/native/cuda/Loss.cu:111: block: [61,0,0], thread: [31,0,0] Assertion input_val >= zero && input_val <= one failed.
0%| | 0/300 [07:18<?, ?it/s]
Traceback (most recent call last):
File "D:/doc/yolox-pytorch-from-scratch/train.py", line 80, in
train(model=model,
File "D:\doc\yolox-pytorch-from-scratch\utils\utils_fit.py", line 94, in train
loss, val_loss, lr = fit_one_epoch(model, yolo_loss, optimizer, epoch, gen, gen_val, writer)
File "D:\doc\yolox-pytorch-from-scratch\utils\utils_fit.py", line 24, in fit_one_epoch
loss_value = yolo_loss(outputs, targets)
File "C:\Users\wzr\miniconda3\lib\site-packages\torch\nn\modules\module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "D:\doc\yolox-pytorch-from-scratch\nets\yolo_training.py", line 270, in forward
return self.get_losses(x_shifts, y_shifts, expanded_strides, labels, outputs)
File "D:\doc\yolox-pytorch-from-scratch\nets\yolo_training.py", line 344, in get_losses
= self.get_assignments(
File "C:\Users\wzr\miniconda3\lib\site-packages\torch\autograd\grad_mode.py", line 28, in decorate_context
return func(*args, **kwargs)
File "D:\doc\yolox-pytorch-from-scratch\nets\yolo_training.py", line 444, in get_assignments
num_fg, gt_matched_classes, pred_ious_this_matching, matched_gt_inds = dynamic_k_matching(
File "D:\doc\yolox-pytorch-from-scratch\nets\yolo_training.py", line 206, in dynamic_k_matching
_, pos_idx = torch.topk(cost[gt_idx], k=dynamic_ks[gt_idx].item(), largest=False)
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.
看到这一句"input_val >= zero && input_val <= one"，我又看了pytorch源码，是求bce损失出的问题，可我用的是nn.BCEWithLogitsLoss，应该不需要0到1啊，标签是没问题的，同样的数据在其他模型跑过，而且运行的时候一开始是正常的，后来才报错的
