criterion_modality = torch.nn.BCEWithLogitsLoss() label = Variable(label.cuda()) loss = criterion_modality(outRGB, label) # 出错行
File "C:\Users\Rain\AppData\Local\Programs\Python\Anaconda.3.5.1\envs\python35\python35\lib\site-packages\torch\nn\modules\module.py", line 491, in __call__ result = self.forward(*input, **kwargs) File "C:\Users\Rain\AppData\Local\Programs\Python\Anaconda.3.5.1\envs\python35\python35\lib\site-packages\torch\nn\modules\loss.py", line 500, in forward reduce=self.reduce) File "C:\Users\Rain\AppData\Local\Programs\Python\Anaconda.3.5.1\envs\python35\python35\lib\site-packages\torch\nn\functional.py", line 1514, in binary_cross_entropy_with_logits raise ValueError("Target size ({}) must be the same as input size ({})".format(target.size(), input.size())) ValueError: Target size (torch.Size([32])) must be the same as input size (torch.Size([32, 2]))
input 和 target 尺寸不匹配,参见官网