input and target shapes do not match: input [1 x 1], target [1] at /pytorch/aten/src/THCUNN/generic/MSECriterion.cu:15

[kevinchow1993]

real A: torch.Size([1, 3, 256, 256]) real_B: torch.Size([1, 3, 256, 256]) Traceback (most recent call last): File "train.py", line 118, in loss_GAN_A2B = criterion_GAN(pred_fake, target_real) File "/home/z00495072/anaconda3/envs/centernet/lib/python3.6/site-packages/torch/nn/modules/module.py", line 491, in call result = self.forward(*input, **kwargs) File "/home/z00495072/anaconda3/envs/centernet/lib/python3.6/site-packages/torch/nn/modules/loss.py", line 372, in forward return F.mse_loss(input, target, size_average=self.size_average, reduce=self.reduce) File "/home/z00495072/anaconda3/envs/centernet/lib/python3.6/site-packages/torch/nn/functional.py", line 1569, in mse_loss input, target, size_average, reduce) File "/home/z00495072/anaconda3/envs/centernet/lib/python3.6/site-packages/torch/nn/functional.py", line 1537, in _pointwise_loss return lambd_optimized(input, target, size_average, reduce) RuntimeError: input and target shapes do not match: input [1 x 1], target [1] at /pytorch/aten/src/THCUNN/generic/MSECriterion.cu:15