Thanks for the update.

Based on your provided code you could use broadcasting and multiply the input tensor as:

```
T = torch.ones(3,3)
for i in range(3):
for j in range(3):
T[i][j] = j*i
print(T)
> tensor([[0., 0., 0.],
[0., 1., 2.],
[0., 2., 4.]])
a = torch.arange(3)
res = a * a.unsqueeze(1)
print(res)
> tensor([[0, 0, 0],
[0, 1, 2],
[0, 2, 4]])
a = torch.arange(100)
res = a * a.unsqueeze(1)
print(res)
> tensor([[ 0, 0, 0, ..., 0, 0, 0],
[ 0, 1, 2, ..., 97, 98, 99],
[ 0, 2, 4, ..., 194, 196, 198],
...,
[ 0, 97, 194, ..., 9409, 9506, 9603],
[ 0, 98, 196, ..., 9506, 9604, 9702],
[ 0, 99, 198, ..., 9603, 9702, 9801]])
```