def test_debug_print_option_totals_color(self):
prob = Problem()
prob.model = FanInGrouped()
prob.model.linear_solver = LinearBlockGS()
prob.model.sub.linear_solver = LinearBlockGS()
prob.model.add_design_var('iv.x1', parallel_deriv_color='par_dv')
prob.model.add_design_var('iv.x2', parallel_deriv_color='par_dv')
prob.model.add_design_var('iv.x3')
prob.model.add_objective('c3.y')
prob.driver.options['debug_print'] = ['totals']
prob.setup(check=False, mode='fwd')
prob.set_solver_print(level=0)
prob.run_driver()
indep_list = ['iv.x1', 'iv.x2', 'iv.x3']
unknown_list = ['c3.y']
stdout = sys.stdout
strout = StringIO()
sys.stdout = strout
try:
_ = prob.compute_totals(unknown_list, indep_list, return_format='flat_dict',
debug_print=not prob.comm.rank)
finally:
sys.stdout = stdout
output = strout.getvalue()
if not prob.comm.rank:
self.assertTrue('Solving color: par_dv (iv.x1, iv.x2)' in output)
self.assertTrue('Solving variable: iv.x3' in output)
def test_fan_in_parallel_sets_fwd(self):
prob = om.Problem()
prob.model = FanInGrouped()
# An extra unconnected desvar was in the original test.
prob.model.add_subsystem('p',
om.IndepVarComp('x3', 0.0),
promotes=['x3'])
prob.model.linear_solver = om.LinearBlockGS()
prob.model.sub.linear_solver = om.LinearBlockGS()
prob.model.add_design_var('x1', parallel_deriv_color='par_dv')
prob.model.add_design_var('x2', parallel_deriv_color='par_dv')
prob.model.add_design_var('x3')
prob.model.add_objective('c3.y')
prob.setup(check=False, mode='fwd')
prob.run_driver()
indep_list = ['x1', 'x2']
unknown_list = ['c3.y']
J = prob.compute_totals(unknown_list,
indep_list,
return_format='flat_dict')
assert_near_equal(J['c3.y', 'x1'][0][0], -6.0, 1e-6)
assert_near_equal(J['c3.y', 'x2'][0][0], 35.0, 1e-6)
def test_debug_print_option_totals_color(self):
prob = om.Problem()
prob.model = FanInGrouped()
# An extra unconnected desvar was in the original test.
prob.model.add_subsystem('p',
om.IndepVarComp('x3', 0.0),
promotes=['x3'])
prob.model.linear_solver = om.LinearBlockGS()
prob.model.sub.linear_solver = om.LinearBlockGS()
prob.model.add_design_var('x1', parallel_deriv_color='par_dv')
prob.model.add_design_var('x2', parallel_deriv_color='par_dv')
prob.model.add_design_var('x3')
prob.model.add_objective('c3.y')
prob.driver.options['debug_print'] = ['totals']
prob.setup(check=False, mode='fwd')
prob.set_solver_print(level=0)
prob.run_driver()
indep_list = ['x1', 'x2', 'x3']
unknown_list = ['c3.y']
stdout = sys.stdout
strout = StringIO()
sys.stdout = strout
try:
_ = prob.compute_totals(unknown_list,
indep_list,
return_format='flat_dict',
debug_print=not prob.comm.rank)
finally:
sys.stdout = stdout
output = strout.getvalue()
if not prob.comm.rank:
self.assertTrue('Solving color: par_dv (x1, x2)' in output)
self.assertTrue(
'In mode: fwd, Solving variable(s) using simul coloring:' in
output)
self.assertTrue("('p.x3', [2])" in output)
def test_minprocs_error(self):
prob = Problem(FanInGrouped())
# require 2 procs for the ParallelGroup
prob.model._proc_info['sub'] = (2, None, 1.0)
# run cases on all procs
prob.driver = DOEDriver(FullFactorialGenerator(levels=3))
prob.driver.options['parallel'] = True
with self.assertRaises(RuntimeError) as context:
prob.setup()
self.assertEqual(
str(context.exception),
": MPI process allocation failed: can't meet min_procs "
"required for the following subsystems: ['sub']")
def test_fan_in_grouped(self):
from openmdao.api import Problem
from openmdao.test_suite.groups.parallel_groups import FanInGrouped
from openmdao.api import DOEDriver, FullFactorialGenerator
from openmdao.api import SqliteRecorder, CaseReader
from mpi4py import MPI
prob = Problem(FanInGrouped())
model = prob.model
model.add_design_var('iv.x1', lower=0.0, upper=1.0)
model.add_design_var('iv.x2', lower=0.0, upper=1.0)
model.add_objective('c3.y')
prob.driver = DOEDriver(FullFactorialGenerator(levels=3))
prob.driver.add_recorder(SqliteRecorder("cases.sql"))
# run 2 cases at a time, each using 2 of our 4 procs
doe_parallel = prob.driver.options['parallel'] = 2
prob.setup()
prob.run_driver()
prob.cleanup()
rank = MPI.COMM_WORLD.rank
# check recorded cases from each case file
if rank < doe_parallel:
filename = "cases.sql_%d" % rank
cases = CaseReader(filename).driver_cases
values = []
for n in range(cases.num_cases):
outputs = cases.get_case(n).outputs
values.append(
(outputs['iv.x1'], outputs['iv.x2'], outputs['c3.y']))
self.assertEqual(
"\n" + "\n".join([
"iv.x1: %5.2f, iv.x2: %5.2f, c3.y: %6.2f" % (x1, x2, y)
for x1, x2, y in values
]), self.expect_text)
def test_fan_in_serial_sets_rev(self):
prob = Problem()
prob.model = FanInGrouped()
prob.model.linear_solver = LinearBlockGS()
prob.model.sub.linear_solver = LinearBlockGS()
prob.model.add_design_var('iv.x1')
prob.model.add_design_var('iv.x2')
prob.model.add_objective('c3.y')
prob.setup(vector_class=vector_class, check=False, mode='rev')
prob.run_driver()
indep_list = ['iv.x1', 'iv.x2']
unknown_list = ['c3.y']
J = prob.compute_totals(unknown_list, indep_list, return_format='dict')
assert_rel_error(self, J['c3.y']['iv.x1'][0][0], -6.0, 1e-6)
assert_rel_error(self, J['c3.y']['iv.x2'][0][0], 35.0, 1e-6)
def test_fan_in_serial_sets_fwd(self):
prob = om.Problem()
prob.model = FanInGrouped()
prob.model.linear_solver = om.LinearBlockGS()
prob.model.sub.linear_solver = om.LinearBlockGS()
prob.model.add_design_var('iv.x1')
prob.model.add_design_var('iv.x2')
prob.model.add_objective('c3.y')
prob.setup(check=False, mode='fwd')
prob.run_driver()
indep_list = ['iv.x1', 'iv.x2']
unknown_list = ['c3.y']
J = prob.compute_totals(unknown_list, indep_list, return_format='flat_dict')
assert_near_equal(J['c3.y', 'iv.x1'][0][0], -6.0, 1e-6)
assert_near_equal(J['c3.y', 'iv.x2'][0][0], 35.0, 1e-6)
def test_fan_in_parallel_sets_fwd(self):
prob = Problem()
prob.model = FanInGrouped()
prob.model.linear_solver = LinearBlockGS()
prob.model.get_subsystem('sub').linear_solver = LinearBlockGS()
prob.model.add_design_var('iv.x1', parallel_deriv_color='par_dv')
prob.model.add_design_var('iv.x2', parallel_deriv_color='par_dv')
prob.model.add_design_var('iv.x3')
prob.model.add_objective('c3.y')
prob.setup(vector_class=vector_class, check=False, mode='fwd')
prob.run_driver()
indep_list = ['iv.x1', 'iv.x2']
unknown_list = ['c3.y']
J = prob.compute_totals(unknown_list, indep_list, return_format='flat_dict')
assert_rel_error(self, J['c3.y', 'iv.x1'][0][0], -6.0, 1e-6)
assert_rel_error(self, J['c3.y', 'iv.x2'][0][0], 35.0, 1e-6)
def test_fan_in_grouped(self):
# Test derivatives for fan-in-grouped topology.
prob = Problem()
prob.model = FanInGrouped()
prob.model.linear_solver = self.linear_solver_class()
prob.set_solver_print(level=0)
prob.setup(check=False, mode='fwd')
prob.run_model()
wrt = ['iv.x1', 'iv.x2']
of = ['c3.y']
J = prob.compute_totals(of=of, wrt=wrt, return_format='flat_dict')
assert_near_equal(J['c3.y', 'iv.x1'], [[-6.0]], 1e-6)
assert_near_equal(J['c3.y', 'iv.x2'], [[35.0]], 1e-6)
prob.setup(check=False, mode='rev')
prob.run_model()
J = prob.compute_totals(of=of, wrt=wrt, return_format='flat_dict')
assert_near_equal(J['c3.y', 'iv.x1'], [[-6.0]], 1e-6)
assert_near_equal(J['c3.y', 'iv.x2'], [[35.0]], 1e-6)
def test_fan_in_grouped_serial(self):
# run cases on all procs (parallel model will run on single proc)
doe_parallel = True
prob = Problem(FanInGrouped())
model = prob.model
model.add_design_var('iv.x1', lower=0.0, upper=1.0)
model.add_design_var('iv.x2', lower=0.0, upper=1.0)
model.add_objective('c3.y')
prob.driver = DOEDriver(FullFactorialGenerator(levels=3))
prob.driver.add_recorder(SqliteRecorder("cases.sql"))
prob.driver.options['parallel'] = doe_parallel
prob.setup(check=False)
failed, output = run_driver(prob)
self.assertFalse(failed)
prob.cleanup()
expected = {
0: {
'iv.x1': np.array([0.]),
'iv.x2': np.array([0.]),
'c3.y': np.array([0.0])
},
1: {
'iv.x1': np.array([.5]),
'iv.x2': np.array([0.]),
'c3.y': np.array([-3.0])
},
2: {
'iv.x1': np.array([1.]),
'iv.x2': np.array([0.]),
'c3.y': np.array([-6.0])
},
3: {
'iv.x1': np.array([0.]),
'iv.x2': np.array([.5]),
'c3.y': np.array([17.5])
},
4: {
'iv.x1': np.array([.5]),
'iv.x2': np.array([.5]),
'c3.y': np.array([14.5])
},
5: {
'iv.x1': np.array([1.]),
'iv.x2': np.array([.5]),
'c3.y': np.array([11.5])
},
6: {
'iv.x1': np.array([0.]),
'iv.x2': np.array([1.]),
'c3.y': np.array([35.0])
},
7: {
'iv.x1': np.array([.5]),
'iv.x2': np.array([1.]),
'c3.y': np.array([32.0])
},
8: {
'iv.x1': np.array([1.]),
'iv.x2': np.array([1.]),
'c3.y': np.array([29.0])
},
}
rank = prob.comm.rank
size = prob.comm.size // doe_parallel
num_cases = 0
# cases will be split across files for each proc up to the number requested
filename = "cases.sql_%d" % rank
expect_msg = "Cases from rank %d are being written to %s." % (rank,
filename)
self.assertTrue(expect_msg in output)
cases = CaseReader(filename).driver_cases
# cases recorded on this proc
num_cases = cases.num_cases
self.assertEqual(num_cases,
len(expected) // size + (rank < len(expected) % size))
for n in range(num_cases):
idx = n * size + rank # index of expected case
outputs = cases.get_case(n).outputs
self.assertEqual(outputs['iv.x1'], expected[idx]['iv.x1'])
self.assertEqual(outputs['iv.x2'], expected[idx]['iv.x2'])
self.assertEqual(outputs['c3.y'], expected[idx]['c3.y'])
# total number of cases recorded across all requested procs
num_cases = prob.comm.allgather(num_cases)
self.assertEqual(sum(num_cases), len(expected))