Thank you very much for the information.
I should admit that it is my first week to start on pytorch and I found this forums extremely valuable learning source.
I have a toy data-set to classify dog images when I perform normalization as mentioned above and without changing any other settings on data loaders
dataiter = iter(load_data['train'])
images, labels = dataiter.next()
images = images.numpy() 
fig = plt.figure(figsize=(20, 4))
for idx in np.arange(10):
    ax = fig.add_subplot(2, 10/2, idx+1, xticks=[], yticks=[])
    plt.imshow(np.transpose(images[idx], (1, 2, 0)))
    ax.set_title(class_names[labels[idx]])

I get this result as shown in the image 
Screenshot from 2019-05-14 11-49-54.png794×172 139 KB

When I delete the normalization it plots normal dog images. When I print the tensor I can see values are positive between [0-1] for input data, after normalization they become between [-1 1]
I do not know if it’s the error of normalization or matplotlib snippet ?
torch version is 0.41 python 3.5