Can you please give me a clue ?
below u can see my DataLoader codes:
class CustomDataset(torch.utils.data.Dataset):
def init(self, data):
self.data = data
def __getitem__(self, index):
    return self.data[index]

def __len__(self):
    return len(self.data)

x = data_ll
separation = int(x.shape[0] * 0.8)
train = x[:separation]
test = x[separation:]
train_dataset = CustomDataset(train)
test_dataset = CustomDataset(test)
train_loader_ll = torch.utils.data.DataLoader(train_dataset, batch_size=2621,shuffle = False)
test_loader_ll = torch.utils.data.DataLoader(test_dataset, batch_size=655,shuffle = False)
print ("//////////////////////////Training dataset//////////////////////////")
for train_sample in train_loader_ll:
print(train_sample.shape)
print ("//////////////////////////Test dataset//////////////////////////")
for test_sample in test_loader_ll:
print(test_sample.shape)
Basically I use this twice. One for noisy data and the other for noiseless data.