refactor: PyTorchInference initialization

[arjun-234]

In this version, I have modified the code by combining two loops into a single loop within the same method. This enhancement has resulted in improved efficiency.

[ExtReMLapin]

Source : It was revealed to me in a dream

Jokes aside, list comprehensions are faster in python, unless the iterator costs a lot, I doubt it will be faster

[arjun-234]

Hello @ExtReMLapin,
I appreciate your question. While list comprehensions are faster in python, I consolidated two loops into one to improve time complexity from O(2) to O(1). This should notably reduce overhead and improve performance, especially with larger inputs.
Thanks :)

[threeal]

@arjun-234 your code lacks another thing that may make it slower than just using list comprehension.

Basically this:

arr = [0] * length
for i in range(length):
    arr[i] = input[i]

Is faster than this:

arr = []
for i in range(length):
    arr.append(input[i])

But still, list comprehension is the fastest of them all. And not only that, it also looks cleaner 👌.

[arjun-234]

Greetings @threeal,
Yeah, you're correct that list comprehensions are always faster, but especially with larger inputs, having fewer iterations is always good, which improves performance in terms of time complexity.
Thanks :)

[itsRoman]

Hello @ExtReMLapin, I appreciate your question. While list comprehensions are faster in python, I consolidated two loops into one to improve time complexity from O(2) to O(1). This should notably reduce overhead and improve performance, especially with larger inputs. Thanks :)

O(2) == O(1) 🤔