Normalize the mnist train data in the Torch tutorial

normalize_torch_mnist_data.lua

require('torch')
-- Find the average per image
train = torch.load('mnist.t7/train_32x32.t7', 'ascii')
train.data = train.data:type(torch.getdefaulttensortype())
BOUND = 60000 -- Perform on the full data
-- BOUND = 1 -- You can test on a single image as a beginning
for index = 1, BOUND do
    cells = train.data[index][1]
    avg = 0
    
    mean = cells:mean()
    std  = cells:std()
    
    cells = (cells - mean) / std
    train.data[index][1] = cells
end