Modules and numpy.random seeds

I have two modules, the first of which which is:

# module.py

import numpy
import myrandom

class A():
    def __init__(self,n1,n2):
        A.rng_set1 = myrandom.generate_random(n1)
        A.rng_set2 = myrandom.generate_random(n2)
        A.data = np.concatenate((A.rng_set1,A.rng_set2))

The module myrandom is something like:

# myrandom.py

import numpy as np

    def generate_random(n):
        return np.random.rand(n)

Given a seed I want A.data to be predictable. I don't want rng_set1 and rng_set2 to share the same numbers if n1 equals n2. I don't understand how to seed this thing.

I've tried putting np.random.seed(constant) into generate_random, into A's init, at module.py top level and before import module.py. I can't seem to get the desired result.

How am i supposed to do this? Thank you.