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训练多种类数据时,出现tensor.size错误

**File "C:\Users\Windows\Desktop\项目1\UNet-master\train.py", line 141, in
main()
File "C:\Users\Windows\Desktop\项目1\UNet-master\train.py", line 137, in main
iterRun.run()
File "C:\Users\Windows\Desktop\项目1\UNet-master\utils\RunEpoch.py", line 28, in run
self.train()
File "C:\Users\Windows\Desktop\项目1\UNet-master\utils\RunEpoch.py", line 51, in train
loss_single[loss_ids] += self.loss[loss_ids](output, target)
File "C:\Users\Windows\anaconda3\envs\torch2\lib\site-packages\torch\nn\modules\module.py", line 1501, in _call_impl
return forward_call(*args, kwargs)
File "C:\Users\Windows\Desktop\项目1\UNet-master\NetWorkRegistry\loss\FocalLoss.py", line 39, in forward
loss = -1 * self.alpha * torch.pow(class_neg_pt, self.gamma) * torch.log(class_pt)
RuntimeError: The size of tensor a (2) must match the size of tensor b (3) at non-singleton dimension 1

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