I have calculated the mean and std for normalization using following code
mean = 0.

std = 0.

nb_samples = 0.

for data,_ in train_loader:

    batch_samples = data.size(0)

    data = data.view(batch_samples, data.size(1), -1)

    mean += data.mean(2).sum(0)

    std += data.std(2).sum(0)

    nb_samples += batch_samples

mean /= nb_samples

std /= nb_samples

I got these values

[0.5820, 0.4512, 0.4023], [0.2217, 0.1858, 0.1705]

when I put the values, it gives me this warning

Clipping input data to the valid range for imshow with RGB data ([0…1] for floats or [0…255] for integers).

But if I used the values calculated for imagenet dataset subset, it does not give warning.
So which values should I use?