torch.logical_and
torch.logical_and(input, other, *, out=None) -> Tensor
Computes the element-wise logical AND of the given input tensors.
   Zeros are treated as "False" and nonzeros are treated as "True".
Parameters:
      * input (Tensor) -- the input tensor.
  * **other** (*Tensor*) -- the tensor to compute AND with

Keyword Arguments:
      out (Tensor, optional) -- the output tensor.
Example:
  >>> torch.logical_and(torch.tensor([True, False, True]), torch.tensor([True, False, False]))
  tensor([ True, False, False])
  >>> a = torch.tensor([0, 1, 10, 0], dtype=torch.int8)
  >>> b = torch.tensor([4, 0, 1, 0], dtype=torch.int8)
  >>> torch.logical_and(a, b)
  tensor([False, False,  True, False])
  >>> torch.logical_and(a.double(), b.double())
  tensor([False, False,  True, False])
  >>> torch.logical_and(a.double(), b)
  tensor([False, False,  True, False])
