def testImportModuleAs(self):
pmi.exec_("import random as s")
# check that it's loaded
self.assert_(hasattr(pmi, "s"))
self.assertEqual(pmi.s.__name__, "random")
# clean up
pmi.exec_("del(s)")
def testLambda(self):
pmi.exec_("myadd = lambda a,b: a+b")
res = pmi.reduce("myadd", mockFunc)
if pmi.isController:
self.assertEqual(res, 42 * pmi.size)
else:
self.assertEqual(res, None)
pmi.exec_("del myadd")
def testImportModule(self):
pmi.exec_("import random")
# check that it's loaded into pmi
self.assert_(hasattr(pmi, "random"))
# check that the main namespace is not polluted
try:
exec "n=random.__name__"
self.fail("expected a NameError")
except NameError:
pass
else:
self.fail("expected a NameError")
# clean up
pmi.exec_("del(random)")
# check that it's gone
self.assertFalse(hasattr(pmi, "random"))
# Copyright 2014 Pierre de Buyl
#
# This file is part of pmi-h5py
#
# pmi-h5py is free software and is licensed under the modified BSD license (see
# LICENSE file).
import pmi
from mpi4py import MPI
pmi.exec_('import test_pmi_mod')
import numpy as np
import h5py
class MyTestLocal(object):
def __init__(self, filename, n):
self.filename = filename
self.f = h5py.File(self.filename,
'w',
driver='mpio',
comm=MPI.COMM_WORLD)
self.n = n
self.data = np.random.random(n)
def show(self):
print MPI.COMM_WORLD.rank, self.data
def fill(self):
self.f.create_dataset('ds1',
dtype=self.data.dtype,
shape=(MPI.COMM_WORLD.size * self.n, ),
import pmi
pmi.setup(2)
# create the parallel function
pmi.exec_(
"""
from mpi4py import MPI
def hello_parallel(name):
return 'Hello %s, this is MPI task %d!' % (name, MPI.COMM_WORLD.rank)
"""
)
# invoke the function on all workers and get the results as a list
res = pmi.invoke("hello_parallel", "Olaf")
print("\n".join(res))
def testCommandMismatch(self):
if pmi.isController:
pmi.exec_("pass")
else:
self.assertRaises(pmi.UserError, pmi.call, None)
# Copyright 2014 Pierre de Buyl
#
# This file is part of pmi-h5py
#
# pmi-h5py is free software and is licensed under the modified BSD license (see
# LICENSE file).
import pmi
from mpi4py import MPI
pmi.exec_('import test_pmi_mod')
import numpy as np
import h5py
class MyTestLocal(object):
def __init__(self, filename, n):
self.filename = filename
self.f = h5py.File(
self.filename, 'w',
driver='mpio', comm=MPI.COMM_WORLD)
self.n = n
self.data = np.random.random(n)
def show(self):
print MPI.COMM_WORLD.rank, self.data
def fill(self):
self.f.create_dataset('ds1',
dtype=self.data.dtype,
shape=(MPI.COMM_WORLD.size*self.n,),
chunks=(self.n,))