def test_set_stderr_level():
stderr_level = libE_logger.get_stderr_level()
assert stderr_level == 35, "Default stderr copying level is 35, found " + \
str(stderr_level)
libE_logger.set_stderr_level('DEBUG')
stderr_level = libE_logger.get_stderr_level()
assert stderr_level == 10, "Log level should be 10. Found: " + str(
stderr_level)
libE_logger.set_stderr_level('INFO')
stderr_level = libE_logger.get_stderr_level()
assert stderr_level == 20, "Log level should be 20. Found: " + str(
stderr_level)
libE_logger.set_stderr_level('WARNING')
stderr_level = libE_logger.get_stderr_level()
assert stderr_level == 30, "Log level should be 30. Found: " + str(
stderr_level)
libE_logger.set_stderr_level('MANAGER_WARNING')
stderr_level = libE_logger.get_stderr_level()
assert stderr_level == 35, "Log level should be 35. Found: " + str(
stderr_level)
libE_logger.set_stderr_level('ERROR')
stderr_level = libE_logger.get_stderr_level()
assert stderr_level == 40, "Log level should be 40. Found: " + str(
stderr_level)
libE_logger.set_level('ERROR')
logger = logging.getLogger('libensemble')
logger.manager_warning('This test message should not log')
def test_set_log_level():
# Default
level = libE_logger.get_level()
assert level == 20, "Log level should be 20. Found: " + str(level)
libE_logger.set_level('DEBUG')
level = libE_logger.get_level()
assert level == 10, "Log level should be 10. Found: " + str(level)
libE_logger.set_level('WARNING')
level = libE_logger.get_level()
assert level == 30, "Log level should be 30. Found: " + str(level)
libE_logger.set_level('MANAGER_WARNING')
level = libE_logger.get_level()
assert level == 35, "Log level should be 35. Found: " + str(level)
libE_logger.set_level('ERROR')
level = libE_logger.get_level()
assert level == 40, "Log level should be 40. Found: " + str(level)
libE_logger.set_level('INFO')
level = libE_logger.get_level()
assert level == 20, "Log level should be 20. Found: " + str(level)
# python3 test_mpi_runners.py --nworkers 3 --comms tcp
#
# The number of concurrent evaluations of the objective function will be 4-1=3.
# """
import os
import numpy as np
from libensemble.message_numbers import WORKER_DONE
from libensemble.libE import libE
from libensemble.gen_funcs.sampling import uniform_random_sample as gen_f
from libensemble.tools import parse_args, add_unique_random_streams
from libensemble.executors.mpi_executor import MPIExecutor
from libensemble import libE_logger
# libE_logger.set_level('DEBUG') # For testing the test
libE_logger.set_level('INFO')
# Do not change these lines - they are parsed by run-tests.sh
# TESTSUITE_COMMS: mpi local
# TESTSUITE_NPROCS: 2 4
nodes_per_worker = 2
def exp_nodelist_for_worker(exp_list, workerID):
"""Modify expected node-lists based on workerID"""
comps = exp_list.split()
new_line = []
for comp in comps:
if comp.startswith('node-'):
new_node_list = []
{% if fail_on_submit is defined %}
FAIL_ON_SUBMIT = {{ fail_on_submit }}
{% else %}
FAIL_ON_SUBMIT = False
{% endif %}
if PERSIS_GEN:
from libensemble.gen_funcs.persistent_uniform_sampling import persistent_uniform as gen_f
from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
else:
from libensemble.gen_funcs.sampling import uniform_random_sample as gen_f
from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first as alloc_f
libE_logger.set_level('DEBUG') # INFO is now default
nworkers, is_master, libE_specs, _ = parse_args()
if is_master:
print('\nRunning with {} workers\n'.format(nworkers))
if not os.path.isfile('./forces.x'):
if os.path.isfile('./build_forces.sh'):
import subprocess
subprocess.check_call(['./build_forces.sh'])
sim_app = os.path.abspath('./forces.x')
# Create executor and register sim to it.
if USE_BALSAM:
from libensemble.executors.balsam_executor import BalsamMPIExecutor
else:
print("you shouldn' hit that")
sys.exit()
from libensemble.tools import parse_args, save_libE_output, \
add_unique_random_streams
from libensemble import libE_logger
if USE_BALSAM:
from libensemble.executors.balsam_executor import BalsamMPIExecutor
exctr = BalsamMPIExecutor(central_mode=True{% if zero_resource_workers is defined %}, zero_resource_workers=[{{ zero_resource_workers }}]{% endif %})
else:
from libensemble.executors.mpi_executor import MPIExecutor
exctr = MPIExecutor(central_mode=True{% if zero_resource_workers is defined %}, zero_resource_workers=[{{ zero_resource_workers }}]{% endif %})
libE_logger.set_level('DEBUG')
nworkers, is_master, libE_specs, _ = parse_args()
# Set to full path of warp executable
sim_app = os.path.abspath({{ sim_app }})
# Problem dimension. This is the number of input parameters exposed,
# that LibEnsemble will vary in order to minimize a single output parameter.
n = 4
exctr.register_calc(full_path=sim_app, calc_type='sim')
# State the objective function, its arguments, output, and necessary parameters
# (and their sizes). Here, the 'user' field is for the user's (in this case,
# the simulation) convenience. Feel free to use it to pass number of nodes,
from libensemble.libE_manager import ManagerException
from libensemble.tools import parse_args, save_libE_output, add_unique_random_streams
from libensemble import libE_logger
from forces_support import test_libe_stats, test_ensemble_dir, check_log_exception
USE_BALSAM = False
PERSIS_GEN = False
if PERSIS_GEN:
from libensemble.gen_funcs.persistent_uniform_sampling import persistent_uniform as gen_f
from libensemble.alloc_funcs.start_only_persistent import only_persistent_gens as alloc_f
else:
from libensemble.gen_funcs.sampling import uniform_random_sample as gen_f
from libensemble.alloc_funcs.give_sim_work_first import give_sim_work_first as alloc_f
libE_logger.set_level('INFO') # INFO is now default
nworkers, is_master, libE_specs, _ = parse_args()
if is_master:
print('\nRunning with {} workers\n'.format(nworkers))
sim_app = os.path.join(os.getcwd(), 'forces.x')
# Normally would be pre-compiled
if not os.path.isfile('forces.x'):
if os.path.isfile('build_forces.sh'):
import subprocess
subprocess.check_call(['./build_forces.sh'])
# Create executor and register sim to it.