How to pass *args to map() function in Python

Question

For example, a toy math function:

def F(x,*args):
    val=0
    for x_ in x:
        val += x_**2
    if val<=args[0]:
        val= -100
    elif val>args[1]:
        val= 100
    return val  

I want to call it inside another function using map to evaluate a list of values:

import numpy as np

if __name__ == "__main__":
    def passf(F, x, *args):
        #do some operations......
        return map(F, x, *args)
    x = np.array([[0,1,2],[10,2,0],[0,0,0]])
    print(list(passf(F, x, 1,100)))

It gave an error TypeError: 'int' object is not iterable. It works if return map(F, x, *args) is changed to list operation return [F(x_, *args) for x_ in x]. But i would like to use map(), since later i am planning to use multiprocessing pool map to evaluate the values in parallel. So is it possible to use map with *args as input parameter?

Edit: So this is the working main part, by using list operation instead of map():

import numpy as np

if __name__ == "__main__":
    def passf(F, x, *args):
        #do some operations......
        return [F(x_, *args) for x_ in x]        
    x = np.array([[0,1,2],[10,2,0],[0,0,0]])
    print(list(passf(F, x, 1,100)))

This outputs:

[5, 100, -100]

Basically F accepts 2D numpy array and positional arguments (*args), each element of the array (which is 1D array) will be evaluated by F and outputs a scalar. So in this case [0,1,2] as input will return 5, [10,2,0] returns 100, and [0,0,0] returns -100. So i want this to be done by using map() as stated above instead of list operation. For passf, it accepts a function F, so i have many different Fs which will be passed to passf, where each F accepts different *args.

Edit 2: added F as input parameter for passf and passf explanation.

Answer 1

Since function F has two two (or more) inputs, you will have to use lambda to be able to use multiple inputs, then call map on that.

def passf_2(x, *args):
    return list(map(lambda x_: F(x_, *args), [x_ for x_ in x]))

You will still have to use list comprehension to break down your array into 1D arrays, but this function should work with your main aim of multiprocessing.