Class variable in multiprocessing - python

Here is my code:

import multiprocessing
import dill

class Some_class():

    class_var = 'Foo'

    def __init__(self, param):
        self.name = param

    def print_name(self):

        print("we are in object "+self.name)
        print(Some_class.class_var)

def run_dill_encoded(what):
    fun, args = dill.loads(what)
    return fun(*args)


def apply_async(pool, fun, args):
    return pool.apply_async(run_dill_encoded, (dill.dumps((fun, args)),))


if __name__ == '__main__':

    list_names = [Some_class('object_1'), Some_class('object_2')]

    pool = multiprocessing.Pool(processes=4)
    results = [apply_async(pool, Some_class.print_name, args=(x,)) for x in list_names]
    output = [p.get() for p in results]
    print(output)

It returns error:

multiprocessing.pool.RemoteTraceback: 
"""
Traceback (most recent call last):
  File "C:\Python34\lib\multiprocessing\pool.py", line 119, in worker
    result = (True, func(*args, **kwds))
  File "C:\...\temp_obj_output_standard.py", line 18, in run_dill_encoded
    return fun(*args)
  File "C:/...temp_obj_output_standard.py", line 14, in print_name
    print(Some_class.class_var)
NameError: name 'Some_class' is not defined
"""

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "C:/...temp_obj_output_standard.py", line 31, in <module>
    output = [p.get() for p in results]
  File "C:/...temp_obj_output_standard.py", line 31, in <listcomp>
    output = [p.get() for p in results]
  File "C:\Python34\lib\multiprocessing\pool.py", line 599, in get
    raise self._value
NameError: name 'Some_class' is not defined

Process finished with exit code 1

The code works fine without line print(Some_class.class_var). What is wrong with accessing class variables, both objects should have it and I don't think processes should conflict about it. Am I missing something? Any suggestions on how to troubleshoot it? Do not worry about run_dill_encoded and apply_async, I am using this solution until I compile multiprocess on Python 3.x.

P.S. This is already enough, but stackoverflow wants me to put more details, not really sure what to put.