multiprocessing.Pool: leak of global named resources using multiprocessing spawn

Bug report

Bug description:

I'm receiving a warning when using the multiprocessing.Pool in spawn mode.

/opt/pyenv/versions/3.12.4/lib/python3.12/multiprocessing/resource_tracker.py:254: UserWarning: resource_tracker: There appear to be 1 leaked semaphore objects to clean up at shutdown
  warnings.warn('resource_tracker: There appear to be %d '

A similar issue was brought up and fixed before, when multiprocessing.Process was used:
https://github.com/python/cpython/pull/30617

The test case introduced by the PR above: https://github.com/python/cpython/blob/3.12/Lib/test/_test_multiprocessing.py#L6040C7-L6040C24

To trigger the warning, I just replaced the Process with Pool as follows:

import multiprocessing as mp
ctx = mp.get_context('spawn')
global_resource = ctx.Semaphore()
def submain(): pass
if __name__ == '__main__':
    p = ctx.Pool(processes=3).starmap(submain, [tuple() for i in range(5)])

CPython versions tested on:

3.11, 3.12, CPython main branch

Operating systems tested on:

Linux

Start with the multiprocessing resource-tracking behavior shown in the report and compare the existing Process fix in PR 30617 with Pool handling. Use the referenced regression test in Lib/test/_test_multiprocessing.py as the starting point, then reproduce the spawn-mode Pool example on Linux. Done means the example no longer reports a leaked semaphore and the behavior is covered by a regression test.