sorry how I can get the target tensors I am using this class to load data
import scipy
import scipy.integrate as integrate
import numpy as np
import os
from scipy import io
import matplotlib.pyplot as plt
from os.path import dirname, join as pjoin
import scipy.io as sio
import matplotlib.pyplot as plt
from torch.autograd import Variable
from os.path import dirname, join as pjoin
import scipy.io as sio

ss=os.path.isdir(root_dirDurringTraining11)
if ss==False:
   os.mkdir(root_dirDurringTraining11)
   
class CMBDataClassifier():

   def __init__(self, root_dirTrain,root_dirTest,split,transforms,debug,CounterIteration,SubID,TPID):
       self.patches, self.labels = None, None
       if split=='train':
           patch_path = os.path.join(root_dirTrain,"Patches"+str(CounterIteration)+".mat")
           label_path = os.path.join(root_dirTrain,"Labels"+str(CounterIteration)+".mat")
           self.patches = scipy.io.loadmat(patch_path)['TrainPatchFinal_4']
           self.labels = scipy.io.loadmat(label_path)['TargetTrainFinal_4']

       else:
           patch_path = os.path.join(root_dirTest,"Patches"+".mat")
           label_path = os.path.join(root_dirTest,"Labels"+".mat")
           self.patches = scipy.io.loadmat(patch_path)['PatchTestFinal']
           
           self.labels = scipy.io.loadmat(label_path)['TargetTestFinal']

       self.split = split
       self.transforms = transforms
       self.debug = debug
       
   def __getitem__(self, index):

       patchF = self.patches[:, :, : , index]

       labelF = self.labels[index].astype(np.float32)
   
       if self.transforms is not None:
           patchF = self.transforms(patchF)

       return patchF,labelF


   def __len__(self):
       return self.patches.shape[-1]````