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Merged
jmlarson1 merged 3 commits into from
Sep 10, 2019
Merged

Feature/petsc blmvm #243

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ff89687
Adding blmvm support for PETSc/TAO
jmlarson1 Aug 2, 2019
70f09d2
flake8
jmlarson1 Aug 2, 2019
d7e5d24
Merge branch 'develop' into feature/petsc_blmvm
jmlarson1 Sep 10, 2019
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60 changes: 32 additions & 28 deletions libensemble/gen_funcs/aposmm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -506,7 +506,7 @@ def advance_local_run(H, gen_specs, c_flag, run, persis_info):
exit_code = 0
display_exception(e)

elif gen_specs['localopt_method'] in ['pounders']:
elif gen_specs['localopt_method'] in ['pounders', 'blmvm']:

if c_flag:
Run_H_F = np.zeros(len(sorted_run_inds), dtype=[('fvec', float, gen_specs['components'])])
Expand All @@ -515,7 +515,10 @@ def advance_local_run(H, gen_specs, c_flag, run, persis_info):
Run_H_F['fvec'][i, :] = H['f_i'][a1]
Run_H = merge_arrays([H[['x_on_cube']][sorted_run_inds], Run_H_F], flatten=True)
else:
Run_H = H[['x_on_cube', 'fvec']][sorted_run_inds]
if gen_specs['localopt_method'] == 'pounders':
Run_H = H[['x_on_cube', 'fvec']][sorted_run_inds]
else:
Run_H = H[['x_on_cube', 'f', 'grad']][sorted_run_inds]

try:
x_opt, exit_code = set_up_and_run_tao(Run_H, gen_specs)
Expand Down Expand Up @@ -653,16 +656,15 @@ def set_up_and_run_tao(Run_H, gen_specs):
"""
tao_comm = MPI.COMM_SELF
n = len(gen_specs['ub'])
m = len(Run_H['fvec'][0])

def pounders_obj_func(tao, X, F, Run_H):
F.array = look_in_history(X.array, Run_H, vector_return=True)
F.array = look_in_history(X.array_r, Run_H, vector_return=True)
return F

# def blmvm_obj_func(tao, X, G, Run_H):
# (f, grad) = look_in_history_fd_grad(X.array, Run_H)
# G.array = grad
# return f
def blmvm_obj_func(tao, X, G, Run_H):
(f, grad) = look_in_history(X.array_r, Run_H)
G.array = grad
return f

# Create starting point, bounds, and tao object
x = PETSc.Vec().create(tao_comm)
Expand All @@ -676,24 +678,26 @@ def pounders_obj_func(tao, X, F, Run_H):
tao = PETSc.TAO().create(tao_comm)
tao.setType(gen_specs['localopt_method'])

# if gen_specs['localopt_method'] == 'pounders':
f = PETSc.Vec().create(tao_comm)
f.setSizes(m)
f.setFromOptions()
if gen_specs['localopt_method'] == 'pounders':
f = PETSc.Vec().create(tao_comm)
f.setSizes(len(Run_H['fvec'][0]))
f.setFromOptions()

delta_0 = gen_specs['dist_to_bound_multiple']*np.min([np.min(ub.array-x.array), np.min(x.array-lb.array)])
delta_0 = gen_specs['dist_to_bound_multiple']*np.min([np.min(ub.array-x.array), np.min(x.array-lb.array)])

PETSc.Options().setValue('-tao_pounders_delta', str(delta_0))
# PETSc.Options().setValue('-pounders_subsolver_tao_type','bqpip')
if hasattr(tao, 'setResidual'):
tao.setResidual(lambda tao, x, f: pounders_obj_func(tao, x, f, Run_H), f)
else:
tao.setSeparableObjective(lambda tao, x, f: pounders_obj_func(tao, x, f, Run_H), f)
# elif gen_specs['localopt_method'] == 'blmvm':
# g = PETSc.Vec().create(tao_comm)
# g.setSizes(n)
# g.setFromOptions()
# tao.setObjectiveGradient(lambda tao, x, g: blmvm_obj_func(tao, x, g, Run_H))
PETSc.Options().setValue('-tao_pounders_delta', str(delta_0))

# PETSc.Options().setValue('-pounders_subsolver_tao_type','bqpip')
if hasattr(tao, 'setResidual'):
tao.setResidual(lambda tao, x, f: pounders_obj_func(tao, x, f, Run_H), f)
else:
tao.setSeparableObjective(lambda tao, x, f: pounders_obj_func(tao, x, f, Run_H), f)

elif gen_specs['localopt_method'] == 'blmvm':
g = PETSc.Vec().create(tao_comm)
g.setSizes(n)
g.setFromOptions()
tao.setObjectiveGradient(lambda tao, x, g: blmvm_obj_func(tao, x, g, Run_H))

# Set everything for tao before solving
PETSc.Options().setValue('-tao_max_funcs', str(len(Run_H)+1))
Expand All @@ -712,10 +716,10 @@ def pounders_obj_func(tao, X, F, Run_H):
# print(tao.view())
# print(x_opt)

# if gen_specs['localopt_method'] == 'pounders':
f.destroy()
# elif gen_specs['localopt_method'] == 'blmvm':
# g.destroy()
if gen_specs['localopt_method'] == 'pounders':
f.destroy()
if gen_specs['localopt_method'] == 'blmvm':
g.destroy()

lb.destroy()
ub.destroy()
Expand Down
11 changes: 9 additions & 2 deletions libensemble/tests/regression_tests/test_6-hump_camel_aposmm_LD_MMA.py
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Original file line number Diff line number Diff line change
Expand Up @@ -72,11 +72,18 @@ def libE_mpi_abort():
quit()

# Perform the run
for run in range(2):
for run in range(3):
if libE_specs['comms'] == 'tcp' and is_master:
libE_specs['worker_cmd'].append(str(run))

if run == 1:
gen_specs['localopt_method'] = 'blmvm'
gen_specs['grtol'] = 1e-5
gen_specs['gatol'] = 1e-5
persis_info = deepcopy(persis_info_safe)

if run == 2:
gen_specs['localopt_method'] = 'LD_MMA'
# Change the bounds to put a local min at a corner point (to test that
# APOSMM handles the same point being in multiple runs) ability to
# give back a previously evaluated point)
Expand All @@ -94,7 +101,7 @@ def libE_mpi_abort():
exit_criteria = {'sim_max': 200, 'elapsed_wallclock_time': 300}
minima = np.array([[-2.9, -1.9]])

persis_info = persis_info_safe
persis_info = deepcopy(persis_info_safe)

H, persis_info, flag = libE(sim_specs, gen_specs, exit_criteria,
persis_info, alloc_specs, libE_specs)
Expand Down