In Convolutional Neural Networks, I've came across some strange functions that take parameters in first parenthesis before taking the input in the second parenthesis.
e.g Fn(parameters=params)(input=x)
Conv2D(filters = F2, kernel_size = 1, strides = (1,1), padding = 'valid', kernel_initializer = initializer(seed=0))(X)
What is this called and why does it exist? Why not simply pass the input in the first part?
According to Geeks for Geeks Higher Order Function is:
A function is called Higher Order Function if it contains other functions as a parameter or returns a function as an output i.e, the functions that operate with another function are known as Higher order Functions. It is worth knowing that this higher order function is applicable for functions and methods as well that takes functions as a parameter or returns a function as a result. Python too supports the concepts of higher order functions.
