Dataloader returns first batch but throws error on the second batch

I am returning three tensors from the getitem function and it only returns the first batch and then start throwing error

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

def __getitem__(self,idx):  

    semihardtriplet = possible_triplets[idx]#Choice the at about 75 % position      

    anchor_t    = self.path_to_tensor(semihardtriplet.anchor,self.device,False) 

    positive_t  = self.path_to_tensor(semihardtriplet.positive,self.device,False)

    negative_t  = self.path_to_tensor(semihardtriplet.negative,self.device,False)


    return anchor_t,positive_t,negative_t

 def path_to_tensor(self,img_path,device,check):

    # img       =


      tensor       = read_image(img_path,ImageReadMode.RGB)


      print("Cant read Image",img_path)


    t = transforms.Compose([transforms.Resize((160,160))])

    tensor    = t(tensor)

    if check:       

      tensor    = tensor.unsqueeze(0)

    tensor    = tensor.float().to(device)

    # tensor    = tensor.permute(0,3,1,2)

    return tensor