Hi everyone,

This is probably an easy question but I didn’t find any explanation on the net. I can’t understand waht the & operator do when applied to tensors like below:

```
a = torch.from_numpy(np.array([[1,2,3],[4,5,6],[7,8,9],[10,11,12]]))
print(a,'\n')
b = torch.from_numpy(np.array([[0,10,10],[10,10,10],[7,8,9],[0,10,12]]))
print(b,'\n')
print(a & b,'\n')
print(b & a)
```

For this test program I get the following output which I can’t understand:

```
tensor([[ 1, 2, 3],
[ 4, 5, 6],
[ 7, 8, 9],
[10, 11, 12]])
tensor([[ 0, 10, 10],
[10, 10, 10],
[ 7, 8, 9],
[ 0, 10, 12]])
tensor([[ 0, 2, 2],
[ 0, 0, 2],
[ 7, 8, 9],
[ 0, 10, 12]])
tensor([[ 0, 2, 2],
[ 0, 0, 2],
[ 7, 8, 9],
[ 0, 10, 12]])
```

Thank you in advance for your explanations!