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torch: multiplication

>>> a = torch.tensor([ 2, 4, 3 ])
>>> a * 3
tensor([ 6, 12,  9])

>>> b = torch.tensor([ 5, 7, 2 ])
>>> torch.mul(a, b)
tensor([10, 28,  6])

>>> a * b
tensor([10, 28,  6])

>>> a = torch.tensor([[ 1, 2, 3, 4 ]])
>>> a
tensor([[1, 2, 3, 4]])

>>> b = torch.tensor([ [40], [30], [20], [10] ])
>>> b
tensor([[40],
        [30],
        [20],
        [10]])

>>> a*b
tensor([[ 40,  80, 120, 160],
        [ 30,  60,  90, 120],
        [ 20,  40,  60,  80],
        [ 10,  20,  30,  40]])

mm

import torch

m1 = torch.tensor([

  [ 0.9  ,  1.3 ],
  [ 4.2  ,  5.2 ],
  [ 2.1  ,  3.0 ]
 
])


m2 = torch.tensor([

  [ 0.1  ,  2.8  ,  3.1  ,  1.8  ,  2.6 ],
  [ 4.8  ,  3.0  ,  0.2  ,  2.5  ,  3.8 ]

])

r = m1.mm(m2)       ; print(r)
r = torch.mm(m1, m2); print(r) # same thing

print(r)
Mutliplying a 3x2 matrix with a 2x5 matrix produces a 3x5 matrix, the ouptut of print(r) is: 
tensor([[ 6.3300,  6.4200,  3.0500,  4.8700,  7.2800],
        [25.3800, 27.3600, 14.0600, 20.5600, 30.6800],
        [14.6100, 14.8800,  7.1100, 11.2800, 16.8600]])

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