报错For debugging consider passing CUDA_LAUNCH_BLOCKING=1.

Nani_xiao2023-11-24 3:04

.报错For debugging consider passing CUDA_LAUNCH_BLOCKING=1.

/aten/src/ATen/native/cuda/NLLLoss2d.cu:103: nll_loss2d_forward_kernel: block: $29,0,0$ , thread: $707,0,0$ Assertion t >= 0 && t < n_classes failed.

报错信息如下：

./aten/src/ATen/native/cuda/NLLLoss2d.cu:103: nll_loss2d_forward_kernel: block: $29,0,0$ , thread: $707,0,0$ Assertion t >= 0 && t < n_classes failed.

。。。。。。

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.

Compile with TORCH_USE_CUDA_DSA to enable device-side assertions.

模型运行训练，可到epoch=9 ，报错

删除models/__pycache__下的缓存文件，重新运行数据集，还是会报错。

解决方案：

是标签有问题，有一张图片标签坏了，某张图片的label标签个数超过了设定的类别数。