In Pytorch, is there a difference between (x<0) and x.lt(0)?

Question

Suppose x is a tensor in Pytorch. One can either write:

x_lowerthanzero = x.lt(0)

or:

x_lowerthanzero = (x<0)

with seemingly the exact same results. Many other operations have Pytorch built-in equivalents: x.gt(0) for (x>0), x.neg() for -x, x.mul() etc.

Is there a good reason to use one form over the other?

Answer 1

They are equivalent. < is simply a more readable alias.

Python operators have canonical function mappings e.g:

Algebraic operations

Operation	Syntax	Function
Addition	a + b	add(a, b)
Subtraction	a - b	sub(a, b)
Multiplication	a * b	mul(a, b)
Division	a / b	truediv(a, b)
Exponentiation	a ** b	pow(a, b)
Matrix Multiplication	a @ b	matmul(a, b)

Comparisons

Operation	Syntax	Function
Ordering	a < b	lt(a, b)
Ordering	a <= b	le(a, b)
Equality	a == b	eq(a, b)
Difference	a != b	ne(a, b)
Ordering	a >= b	ge(a, b)
Ordering	a > b	gt(a, b)

You can check that these are indeed mapped to the respectively named torch functions here e.g:

def __lt__(self, other):
    return self.lt(other)

Answer 2

Usually there is no reason for using one over the other, they are mostly for convenience: Many of those methods do have for instance an out argument, which lets you specify a tensor in which to save the result, but you can just as well do that using the operators instead of the methods.