ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 512, 1, 1])

[meshghi]

Hello,

I tried to use my customized dataset with image size 256x256 and 12 classes. I'm not using your VOC.py and dataloader codes. I am using my own dataloaders as follows but I get this error after some iterations:

ValueError: Expected more than 1 value per channel when training, got input size torch.Size([1, 512, 1, 1]) T (1) | Ls 2.51 Lu 0.00 Lw 0.00 PW 0.00 m1 0.04 m2 0.04|: 1%|▍ | 20/1894 [00:11<18:32, 1.68it/s]

Dataloaders in train.py file:

` num_classes = 12

supervised_data = SLD_Labeled()
other_data = SLD_Unlabeled()


labeled_percentage = 0.2
all_data_size = len(other_data)
labeled_size = math.ceil(labeled_percentage * all_data_size)
unlabeled_size = all_data_size - labeled_size
unsupervised_data, val_data = random_split(other_data, [unlabeled_size, labeled_size])

supervised_loader = DataLoader(dataset=supervised_data,
                                batch_size=4,
                                shuffle=True,
                                )

unsupervised_loader = DataLoader(dataset=unsupervised_data,
                                batch_size=4,
                                shuffle=True,
                                )

val_loader = DataLoader(dataset=val_data,
                        batch_size=4,
                        shuffle=False,
                        )`

[SuzannaLin]

Check Solved Issues #28