def main(budget=budget,
max_runs=max_runs,
current_batch=current_batch,
number_of_batches=number_of_batches):
"""Initialize suite and observer, then benchmark solver by calling
``batch_loop(SOLVER, suite, observer, budget,...``
"""
suite = Suite(suite_name, suite_instance, suite_options)
observer_name = default_observers()[suite_name]
# observer_name = another observer if so desired
observer_options.update_gracefully(default_observer_options())
observer = Observer(observer_name, observer_options.as_string)
print("Benchmarking solver '%s' with budget=%d*dimension on %s suite, %s" %
(' '.join(
str(SOLVER).split()[:2]), budget, suite.name, time.asctime()))
if number_of_batches > 1:
print('Batch usecase, make sure you run *all* %d batches.\n' %
number_of_batches)
t0 = time.clock()
batch_loop(SOLVER, suite, observer, budget, max_runs, current_batch,
number_of_batches)
print(", %s (%s total elapsed time)." %
(time.asctime(), ascetime(time.clock() - t0)))
print('Data written to folder', observer.result_folder)
print('To post-process the data call \n'
' python -m cocopp %s \n'
'from a system shell or \n'
' cocopp.main("%s") \n'
'from a python shell' % (2 * (observer.result_folder, )))
def main(budget=budget,
max_runs=max_runs,
current_batch=current_batch,
number_of_batches=number_of_batches):
"""Initialize suite and observer, then benchmark solver by calling
``batch_loop(SOLVER, suite, observer, budget,...``
"""
suite = Suite(suite_name, suite_instance, suite_options)
observer_name = default_observers()[suite_name]
# observer_name = another observer if so desired
# observer_options.update_gracefully(default_observer_options())
observer = Observer(observer_name, observer_options.as_string)
"""
print("Benchmarking solver '%s' with budget=%d*dimension on %s suite, %s"
% (' '.join(str(SOLVER).split()[:2]), budget,
suite.name, time.asctime()))
if number_of_batches > 1:
print('Batch usecase, make sure you run *all* %d batches.\n' %
number_of_batches)
t0 = time.clock()
"""
batch_loop(SOLVER, suite, observer, budget, max_runs, current_batch,
number_of_batches)
"""
def run(self, budget=100, current_batch=1, number_of_batches=15):
# type: (int, int, int) -> None
suite = Suite(self._suite_name, self._suite_instance,
self._suite_options)
observer_name = default_observers()[self._suite_name]
observer_options = self._build_observer_options(budget)
observer = Observer(observer_name, observer_options.as_string)
for problem_index, problem in enumerate(tqdm(suite)):
if (problem_index % number_of_batches) != current_batch - 1:
continue
observer.observe(problem)
max_evals = budget * problem.dimension
self._solver(problem,
problem.lower_bounds,
problem.upper_bounds,
max_evals - problem.evaluations_constraints,
verbose=False)
