Python's multiprocessing pool does unwanted caching

I want to run the same function (with some random numbers generated inside it) many times by parallelizing the runs over multiple CPUs. I tried using multiprocessing but it seems like the function is running only once. I wonder if some caching is going on that prevents multiple runs from happening. Consider the following simple example.

import numpy as np
import multiprocessing as mp

p = mp.Pool()
vals = p.map(np.random.normal, [0]*5)
p.close()
print(vals)

This gives the output:

[-2.5729019061921052, -2.5729019061921052, -2.5729019061921052, -2.5729019061921052, -2.5729019061921052]

I want the function to run for every element in the list passed to map. How to disable this "caching" or whatever is going on? This issue doesn't arise when I use the built-in map instead of multiprocessing.

I am using python 3.8.8 on WSL.