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***/code/ESPCN-pytorch/venv/lib/python3.7/site-packages/torch/nn/modules/loss.py:445: UserWarning: Using a target size (torch.Size([16, 1, 51, 51])) that is different to the input size (torch.Size([16, 1, 34, 34])). This will likely lead to incorrect results due to broadcasting. Please ensure they have the same size.
return F.mse_loss(input, target, reduction=self.reduction)
Traceback (most recent call last):
File "train.py", line 79, in
loss = criterion(preds, labels)
File "//code/ESPCN-pytorch/venv/lib/python3.7/site-packages/torch/nn/modules/module.py", line 722, in _call_impl
result = self.forward(input, kwargs)
File "//code/ESPCN-pytorch/venv/lib/python3.7/site-packages/torch/nn/modules/loss.py", line 445, in forward
return F.mse_loss(input, target, reduction=self.reduction)
File "//code/ESPCN-pytorch/venv/lib/python3.7/site-packages/torch/nn/functional.py", line 2647, in mse_loss
expanded_input, expanded_target = torch.broadcast_tensors(input, target)
File "/***/code/ESPCN-pytorch/venv/lib/python3.7/site-packages/torch/functional.py", line 65, in broadcast_tensors
return _VF.broadcast_tensors(tensors)
RuntimeError: The size of tensor a (34) must match the size of tensor b (51) at non-singleton dimension 3
I assume that somewhere in the .h5 file there is a hard-coded image that was created using a scale factor of 3. Is that correct? Because it seems that some images are not scaling properly with the dataset provided in the README.md
The text was updated successfully, but these errors were encountered:
python train.py --train-file "/BLAH_BLAH/SR/91-image_x3.h5" --eval-file "/BLAH_BLAHSR/Set5_x3.h5" --outputs-dir "/BLAH_BLAH/model_run/SR_outputs" --scale 2 --lr 1e-3 --batch-size 16 --num-epochs 200 --num-workers 8 --seed 123
epoch: 0/199: 0%| | 0/2688 [00:00<?, ?it/s]
***/code/ESPCN-pytorch/venv/lib/python3.7/site-packages/torch/nn/modules/loss.py:445: UserWarning: Using a target size (torch.Size([16, 1, 51, 51])) that is different to the input size (torch.Size([16, 1, 34, 34])). This will likely lead to incorrect results due to broadcasting. Please ensure they have the same size.
return F.mse_loss(input, target, reduction=self.reduction)
Traceback (most recent call last):
File "train.py", line 79, in
loss = criterion(preds, labels)
File "//code/ESPCN-pytorch/venv/lib/python3.7/site-packages/torch/nn/modules/module.py", line 722, in _call_impl
result = self.forward(input, kwargs)
File "//code/ESPCN-pytorch/venv/lib/python3.7/site-packages/torch/nn/modules/loss.py", line 445, in forward
return F.mse_loss(input, target, reduction=self.reduction)
File "//code/ESPCN-pytorch/venv/lib/python3.7/site-packages/torch/nn/functional.py", line 2647, in mse_loss
expanded_input, expanded_target = torch.broadcast_tensors(input, target)
File "/***/code/ESPCN-pytorch/venv/lib/python3.7/site-packages/torch/functional.py", line 65, in broadcast_tensors
return _VF.broadcast_tensors(tensors)
RuntimeError: The size of tensor a (34) must match the size of tensor b (51) at non-singleton dimension 3
I assume that somewhere in the
.h5
file there is a hard-coded image that was created using a scale factor of 3. Is that correct? Because it seems that some images are not scaling properly with the dataset provided in the README.mdThe text was updated successfully, but these errors were encountered: