The size of tensor a (16384) must match the size of tensor b (49152) at non-singleton dimension 1

[HHDAW]

Hello，thanks for your great work.I had some problems before the model training started.I tried to adjust the image but it didn't work.Please give me some advice.The following is the error message
Traceback (most recent call last):
File "/root/autodl-tmp/XNET/XNet-main/XNet-main/train_semi_XNet.py", line 254, in
loss_train_sup1 = criterion(pred_train_sup1, mask_train_sup)
File "/root/miniconda3/envs/xnet3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "/root/autodl-tmp/XNET/XNet-main/XNet-main/loss/loss_function.py", line 119, in forward
return self._base_forward(output, target_one_hot, valid_mask)
File "/root/autodl-tmp/XNET/XNet-main/XNet-main/loss/loss_function.py", line 92, in _base_forward
dice_loss = dice(predict[:, i], target[..., i], valid_mask)
File "/root/miniconda3/envs/xnet3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 889, in _call_impl
result = self.forward(*input, **kwargs)
File "/root/autodl-tmp/XNET/XNet-main/XNet-main/loss/loss_function.py", line 59, in forward
num = torch.sum(torch.mul(predict, target) * valid_mask, dim=1) * 2 + self.smooth
RuntimeError: The size of tensor a (16384) must match the size of tensor b (49152) at non-singleton dimension 1

[Yanfeng-Zhou]

This error is caused by the inconsistency between image size and mask size.

[HHDAW]

Yes.I read the previous question.But I use the /config/augmentation/online_aug.py to resize the image,it still reports errors.

[Yanfeng-Zhou]

Can you print pred_train_sup1.shape and mask_train_sup.shape. There are some problems with the first dimension of these two tensors.

[HHDAW]

pred_train_sup1.shape([2, 2, 128, 128]) and mask_train_sup.shape ([2, 128, 128, 3, 256])

[Yanfeng-Zhou]

The shape of your mask is very strange. Generally speaking, for 2D images, the image shape is [B, C, H, W] while the mask shape is [B, H, W]. what is the meaning of "3" and "256" in your mask shape.

[HHDAW]

Sorry，I have one more question to ask.
During training,Why is my best printed data inconsistent with my saved model.Saved results are less than optimal