Torchaic tensor logical 'and' reduce syntax

What is the “torchaic” way of reducing a tensor with a logical and?

t = torch.tensor([True,True,True])
f = torch.tensor([True,False,True])

# if t:
    # this is the ideal syntax I want but it
    # throws RuntimeError: Boolean value of Tensor with more than one value is ambiguous

# if torch.and(t):
    # this could also be the ideal syntax I want but it
    # throws SyntaxError: invalid syntax

# this works, but do I really have to write my own function?        
def is_all_true(t):
    r = torch.tensor([True])
    for i in range(len(t)):
        r = torch.bitwise_and(r, t[i])
    return r

if is_all_true(t):
    print("t is all True") # outputs "t is all True"
if not is_all_true(f):
    print("f is not all True") # outputs "f is not all True"

“Torchaic” way:

torch.all(t) # outputs tensor(True)
torch.all(f) # outputs tensor(False)