When I use PyTorch DataLoader to load my test data, I set the shuffle to False like this.
test_loader = DataLoader(test_set, batch_size=batch_size, shuffle=False)
It returns labels like this:
 3
The labels are all 1 which is impossible because my data includes data from different classes(thus, different labels).
When I changed the shuffle argument of DataLoader to shuffle=True,
test_loader = DataLoader(test_set, batch_size=batch_size, shuffle=True)
the labels are finally returned normally.
Labels:  tensor([11,  0, 12,  5, 13, 16, 12, 16, 18,  7, 10, 10,  8, 18, 14, 16, 14,  3,
        15,  6,  0, 10,  6, 10,  0, 18, 14,  0,  7, 10,  5, 15, 11,  7,  0,  9,
        11, 13,  8, 11,  6, 16, 10,  8, 10, 18,  9,  4,  7, 10,  5, 18,  3, 12,
         5,  9,  8,  6, 15,  3, 14, 12, 17, 14])

Labels:  tensor([14, 14,  8, 12, 15,  7,  6, 14,  8,  9, 17, 12, 16,  0, 17,  1,  7,  2,
        16, 14, 10, 15,  7,  8, 14, 16,  4, 17,  9, 15,  6,  6,  6, 18,  5,  0,
         8, 10,  2,  0,  8,  6,  5, 17, 16, 18, 10,  9, 11,  7,  7, 10, 18,  7,
         4,  7,  9,  4, 18,  6, 18,  6,  5, 10])

The problem is solved but I don’t understand why dataloader returns all same labels when shuffle is set to False. Can anyone explain this to me?