How to use transforms for normalization

Lets say I have a tensor named Test
Test = torch.rand(2,3,4,5)

How I can make my tensor to be normalized between and 1 for each channel. In other words, i want to get 0 and 1 for each channel when I do this:

print('The size is: {}, \n \
      1st channel is {}\n \
      min and max are {} and {} \n' 
      .format(Test.size(),Test[0,0,:,:], torch.min(Test[0,0,:,:]), torch.max(Test[0,0,:,:])))

please let me know if I need to use something other than transforms.