我正在尝试从这个存储库中训练 yolo-v3 模型 https://github.com/eriklindernoren/PyTorch-YOLOv3 在我的自定义形状数据集上，但我不断收到错误"运行时错误：CUDA 错误：设备端断言触发">
我尝试查找解决方案并尝试了不同答案中建议的几件事(例如修复注释中类的索引(，但错误仍然存在。
我正在按照存储库自述文件中的描述在自定义数据集上进行训练，并相应地调整了 custom.data 和数据/自定义/。
我一直收到这个输出。
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [32,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [33,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [34,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [35,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [36,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [37,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [38,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [39,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
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C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [44,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [45,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [0,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [1,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [2,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
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C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [4,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [5,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [6,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [7,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [12,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [13,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [14,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [15,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [20,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [21,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [22,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
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C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [24,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [25,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [26,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [27,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [28,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [29,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
C:/w/1/s/windows/pytorch/aten/src/ATen/native/cuda/IndexKernel.cu:60: block: [0,0,0], thread: [31,0,0] Assertion `index >= -sizes[i] && index < sizes[i] && "index out of bounds"` failed.
Traceback (most recent call last):
File "train.py", line 105, in <module>
loss, outputs = model(imgs, targets)
File "C:UsersuserAppDataLocalProgramsPythonPython36libsite-packagestorchnnmodulesmodule.py", line 547, in __call__
result = self.forward(*input, **kwargs)
File "D:DocumentsGPCodeTorchYoloPyTorch-YOLOv3models.py", line 259, in forward
x, layer_loss = module[0](x, targets, img_dim)
File "C:UsersuserAppDataLocalProgramsPythonPython36libsite-packagestorchnnmodulesmodule.py", line 547, in __call__
result = self.forward(*input, **kwargs)
File "D:DocumentsGPCodeTorchYoloPyTorch-YOLOv3models.py", line 188, in forward
ignore_thres=self.ignore_thres,
File "D:DocumentsGPCodeTorchYoloPyTorch-YOLOv3utilsutils.py", line 318, in build_targets
iou_scores[b, best_n, gj, gi] = bbox_iou(pred_boxes[b, best_n, gj, gi], target_boxes, x1y1x2y2=False)
File "D:DocumentsGPCodeTorchYoloPyTorch-YOLOv3utilsutils.py", line 199, in bbox_iou
b1_x1, b1_x2 = box1[:, 0] - box1[:, 2] / 2, box1[:, 0] + box1[:, 2] / 2
RuntimeError: CUDA error: device-side assert triggered
唯一改变的是弄乱火车时数组索引中的"2".jpg类标签索引
b1_x1, b1_x2 = box1[:, 0] - box1[:, 2] / 2, box1[:, 0] + box1[:, 2] / 2
我在谷歌 colab 上训练 resnet 模型时也遇到了这个问题。所以在我的例子中，我在 7 个类上训练模型，但我网络的最后一层设置为输出 3 个类。
因此我改变了
self.classifier = torch.nn.Sequential(torch.nn.BatchNorm1d(512), torch.nn.Linear(512, 3))
对此
self.classifier = torch.nn.Sequential(torch.nn.BatchNorm1d(512), torch.nn.Linear(512, 7))
这样做之后，我仍然收到错误，因为我没有重新启动谷歌 colab。
请记住，每当收到此错误时，请检查两件事：
- class_labels应该从 0 开始，即在我的例子中 [0,1,2,3,4,5,6] 对于 7 个类。
- 检查最终输出图层是否输出了确切的类数。
在那之后，
刷新笔记本以刷新所有 cuda 断言。
出现任何 CUDA 错误后，重新启动笔记本，否则您将继续收到 CUDA 错误，因为前面的断言尚未被清除。通过重新启动笔记本，您将清除所有 cuda 断言。
通常，当您遇到神秘的 CUDA 错误时，您应该切换到 CPU，看看您是否在那里收到更有意义的错误消息。
或者，设置CUDA_LAUNCH_BLOCKING=1以获得信息更丰富的堆栈跟踪(有关详细信息，请参阅此答案(。
有关更多详细信息，请参阅此答案。
我想，在您的情况下，似乎您的除以 2 会在 pytorch 寻找整数的地方创建分数。尝试
b1_x1, b1_x2 = box1[:, 0] - box1[:, 2] // 2, box1[:, 0] + box1[:, 2] // 2
- 在我的情况下，我从 0 开始class_labels：在我的例子中 [0,1,2,3,4] 5节课。
- 然后我刷新了谷歌笔记本，它起作用了。