Stack expects tensor to be equal size, but got [66, 67, 4] at entry 0 and [66, 68, 4] at entry 7

class customDataset(Dataset):
    def __init__(self,csv_file, root_dir, transform=None):
        self.annotations = pd.read_csv(csv_file)
        self.root_dir = root_dir
        #self.transform = transform
        
    def __len__(self):
        return len(self.annotations)
    
    def __getitem__(self,index):
        img_path = os.path.join(self.root_dir,self.annotations.iloc[index,0])
        image = io.imread(img_path)
        y_label = torch.tensor(int(self.annotations.iloc[index,1]))
        
        #if self.transform:
        #    image = self.transform(image)
        return (image,y_label)
        

device = torch.device("cuda")

in_channel = 1
num_classes = 1
learning_rate = 0.001
batch_size = 32
num_epochs = 1

dataset = customDataset(csv_file="biomass.csv", root_dir = "biomassMerged", transform = transforms.ToTensor())

train_set, test_set = torch.utils.data.random_split(dataset, [len(dataset)- 10000,10000])
train_loader = DataLoader(dataset=train_set,batch_size=batch_size,shuffle=True)
test_loader = DataLoader(dataset=test_set,batch_size=batch_size,shuffle=True)

model = torchvision.models.googlenet(pretrained = True)
model.to(device)

criterion = nn.CrossEntropyLoss()
optimizer = optim.Adam(model.parameters(), lr = learning_rate)


for epoch in range(num_epochs):
    losses = []
    
    for batch_idx, (data, targets) in enumerate(train_loader):
        data = data.to(device=device)
        targets = targets.to(device=device)
        
        scores = model(data)
        loss = criterion(scores,targests)
        
        losses.append(loss.item())
        
        optimizer.zero_grad()
        loss.backward()
        
        optimizer.step()
        
    print(f"Cost at each {epoch} is {sum(losses)/len(losses)}")

I have created a customDataset class since I need to go through a lot of image data that I have gathered, the issue is that every time I go through it there is a new entry that tensors dont match. How do I fix this? The images should all be the same size.