rajeevyasarla / umrl--using-cycle-spinning Goto Github PK

I ran the code using pre-trained model python umrl_cycspn_test.py --dataroot ./facades/validation --valDataroot ./facades/validation --netG ./pre_trained/Net_DIDMDN.pth
Got the error
/content/drive/MyDrive/ColabNotebooks/UMRL--using-Cycle-Spinning-master/UMRL--using-Cycle-Spinning-master/umrl_cycspn_test.py:146: UserWarning: volatile was removed and now has no effect. Use with torch.no_grad(): instead.
target = Variable(target, volatile=True)
/content/drive/MyDrive/ColabNotebooks/UMRL--using-Cycle-Spinning-master/UMRL--using-Cycle-Spinning-master/umrl_cycspn_test.py:147: UserWarning: volatile was removed and now has no effect. Use with torch.no_grad(): instead.
input = Variable(input, volatile=True)
/content/drive/MyDrive/ColabNotebooks/UMRL--using-Cycle-Spinning-master/UMRL--using-Cycle-Spinning-master/umrl_cycspn_test.py:148: UserWarning: volatile was removed and now has no effect. Use with torch.no_grad(): instead.
depth = Variable(depth, volatile=True)
/content/drive/MyDrive/ColabNotebooks/UMRL--using-Cycle-Spinning-master/UMRL--using-Cycle-Spinning-master/umrl_cycspn_test.py:149: UserWarning: volatile was removed and now has no effect. Use with torch.no_grad(): instead.
ato = Variable(ato, volatile=True)
/content/drive/MyDrive/ColabNotebooks/UMRL--using-Cycle-Spinning-master/UMRL--using-Cycle-Spinning-master/transforms/pix2pix.py:41: UserWarning: TypedStorage is deprecated. It will be removed in the future and UntypedStorage will be the only storage class. This should only matter to you if you are using storages directly. To access UntypedStorage directly, use tensor.untyped_storage() instead of tensor.storage()
img = torch.ByteTensor(torch.ByteStorage.from_buffer(pic.tobytes()))
Image:0
/content/drive/MyDrive/ColabNotebooks/UMRL--using-Cycle-Spinning-master/UMRL--using-Cycle-Spinning-master/umrl_cycspn_test.py:198: UserWarning: volatile was removed and now has no effect. Use with torch.no_grad(): instead.
val_target = Variable(val_target_cpu, volatile=True)
/content/drive/MyDrive/ColabNotebooks/UMRL--using-Cycle-Spinning-master/UMRL--using-Cycle-Spinning-master/umrl_cycspn_test.py:222: UserWarning: volatile was removed and now has no effect. Use with torch.no_grad(): instead.
val_inputv = Variable(val_inputv, volatile=True)
/usr/local/lib/python3.10/dist-packages/torch/nn/functional.py:4084: UserWarning: nn.functional.upsample_nearest is deprecated. Use nn.functional.interpolate instead.
warnings.warn("nn.functional.upsample_nearest is deprecated. Use nn.functional.interpolate instead.")
count 0
Inside If loop tensor1 size torch.Size([1, 3, 256, 400]) tensor sizetorch.Size([1, 3, 256, 400])

count 1
Inside else loop tensor1 size torch.Size([1, 3, 256, 400]) tensor sizetorch.Size([1, 3, 256, 400])

max_r 267 row 0 max_c 400 col 50

count 2
Inside else loop tensor1 size torch.Size([1, 3, 256, 400]) tensor sizetorch.Size([1, 3, 256, 400])

max_r 267 row 0 max_c 400 col 100

count 3
Inside else loop tensor1 size torch.Size([1, 3, 256, 400]) tensor sizetorch.Size([1, 3, 256, 400])

max_r 267 row 0 max_c 400 col 150

count 4
Inside else loop tensor1 size torch.Size([1, 3, 256, 400]) tensor sizetorch.Size([1, 3, 256, 400])

max_r 267 row 0 max_c 400 col 200

count 5
Inside else loop tensor1 size torch.Size([1, 3, 256, 400]) tensor sizetorch.Size([1, 3, 256, 400])

max_r 267 row 0 max_c 400 col 250

count 6
Inside else loop tensor1 size torch.Size([1, 3, 256, 400]) tensor sizetorch.Size([1, 3, 256, 400])

max_r 267 row 0 max_c 400 col 300

count 7
Inside else loop tensor1 size torch.Size([1, 3, 256, 400]) tensor sizetorch.Size([1, 3, 256, 400])

max_r 267 row 0 max_c 400 col 350

count 8
Inside else loop tensor1 size torch.Size([1, 3, 256, 400]) tensor sizetorch.Size([1, 3, 256, 400])

max_r 267 row 50 max_c 400 col 0

Traceback (most recent call last):
File "/content/drive/MyDrive/ColabNotebooks/UMRL--using-Cycle-Spinning-master/UMRL--using-Cycle-Spinning-master/umrl_cycspn_test.py", line 245, in
tensor[:, :, max_r - row:, max_c - col:] = tensor[:, :, max_r - row:, max_c - col:] + (
RuntimeError: The size of tensor a (39) must match the size of tensor b (50) at non-singleton dimension 2
Kindly help me to resolve this

Hi!

I ran the following test command:

python umrl_test.py --dataroot ./facades/validation --valDataroot ./facades/validation --netG ./pre_trained/Net_DIDMDN.pth

and I received this:

RuntimeError: Sizes of tensors must match except in dimension 2. Got 33 and 32 (The offending index is 0)

I have all the installations as suggested. Please let me know how to solve this.