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benchmark_utils.py
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from optimizers import *
import gc
import time
def experiment_runner(args, x_0_dict):
"""
Runner routine which performs the whole experiment set.
Parameters
----------
args : populated namespace object from ArgumentParser
The system of equations evaluated at point x.
x_0_dict : dict
The dictionary of initial points x.
Returns
-------
dict
Aggregated experiment data.
"""
gc.enable()
gc.collect()
exp_res_dict = dict()
if args.verbose:
print("Started DetGNM!")
exp_res_dict['DetGNM'] = dict()
for oracle_class, name in [(RosenbrockEvenSumOracle, 'Rosenbrock-Skokov'), (HatOracle, 'Hat')]:
if args.verbose:
print('Oracle:', name)
exp_res_dict['DetGNM'][name] = dict()
for n in args.n_dims:
if args.verbose:
print(' n:', n)
exp_res_dict['DetGNM'][name][n] = dict()
for line_search in ["None", "Armijo"]:
if args.verbose:
print(' line_search:', line_search)
exp_res_dict['DetGNM'][name][n][line_search] = dict()
if line_search == "Armijo":
for pair_num, (c1, c2) in enumerate(zip(args.c1_list, args.c2_list)):
if args.verbose:
print(' c1 = {:.4f}, c2 = {:.4f}:'.format(c1, c2))
exp_res_dict['DetGNM'][name][n][line_search][pair_num] = dict()
for i in range(args.n_starts):
if args.verbose:
print(' start #:', i + 1)
start = time.time()
_, f_vals, nabla_f_2_norm_vals, _, _ = DetGNM(oracle_class(n), args.N_iter, x_0_dict[n][i], args.L_0, True, None, line_search, probe_c1=c1, probe_c2=c2)
start = time.time() - start
exp_res_dict['DetGNM'][name][n][line_search][pair_num][i] = {'f_vals': f_vals,
'nabla_f_2_norm_vals': nabla_f_2_norm_vals,
'avg_time_s': start / len(f_vals),
'time_s': start}
del _, f_vals, nabla_f_2_norm_vals, start
gc.collect()
else:
for i in range(args.n_starts):
if args.verbose:
print(' start #:', i + 1)
start = time.time()
_, f_vals, nabla_f_2_norm_vals, _, _ = DetGNM(oracle_class(n), args.N_iter, x_0_dict[n][i], args.L_0, True, None, line_search)
start = time.time() - start
exp_res_dict['DetGNM'][name][n][line_search][i] = {'f_vals': f_vals, 'nabla_f_2_norm_vals': nabla_f_2_norm_vals, 'avg_time_s': start / len(f_vals), 'time_s': start}
del _, f_vals, nabla_f_2_norm_vals, start
gc.collect()
if args.verbose:
print("Started ArmijoAccDetGNM!")
exp_res_dict['ArmijoAccDetGNM'] = dict()
for oracle_class, name in [(RosenbrockEvenSumOracle, 'Rosenbrock-Skokov'), (HatOracle, 'Hat')]:
if args.verbose:
print('Oracle:', name)
exp_res_dict['ArmijoAccDetGNM'][name] = dict()
for n in args.n_dims:
if args.verbose:
print(' n:', n)
exp_res_dict['ArmijoAccDetGNM'][name][n] = dict()
for pair_num, (c1, c2) in enumerate(zip(args.c1_list, args.c2_list)):
if args.verbose:
print(' c1 = {:.4f}, c2 = {:.4f}:'.format(c1, c2))
exp_res_dict['ArmijoAccDetGNM'][name][n][pair_num] = dict()
for line_search in ["None", "Armijo"]:
if args.verbose:
print(' line_search: {}'.format(line_search))
exp_res_dict['ArmijoAccDetGNM'][name][n][pair_num][line_search] = dict()
if line_search == "Armijo":
for probe_pair_num, (probe_c1, probe_c2) in enumerate(zip(args.c1_list, args.c2_list)):
if args.verbose:
print(' c1 = {:.4f}, c2 = {:.4f}:'.format(probe_c1, probe_c2))
exp_res_dict['ArmijoAccDetGNM'][name][n][pair_num][line_search][probe_pair_num] = dict()
for i in range(args.n_starts):
if args.verbose:
print(' start #:', i + 1)
start = time.time()
_, f_vals, nabla_f_2_norm_vals, _, _, local_steps_list, spec_steps_list = AccDetGNM(oracle_class(n), args.N_iter, x_0_dict[n][i], args.L_0, True, None, "Armijo",
line_search, c1=c1, c2=c2, probe_c1=probe_c1, probe_c2=probe_c2)
start = time.time() - start
exp_res_dict['ArmijoAccDetGNM'][name][n][pair_num][line_search][probe_pair_num][i] = {'f_vals': f_vals,
'nabla_f_2_norm_vals': nabla_f_2_norm_vals,
'local_steps_list': local_steps_list,
'spec_steps_list': spec_steps_list,
'avg_time_s': start / len(f_vals),
'time_s': start}
del _, f_vals, nabla_f_2_norm_vals, local_steps_list, spec_steps_list, start
gc.collect()
else:
for i in range(args.n_starts):
if args.verbose:
print(' start #:', i + 1)
start = time.time()
_, f_vals, nabla_f_2_norm_vals, _, _, local_steps_list, spec_steps_list = AccDetGNM(oracle_class(n), args.N_iter, x_0_dict[n][i], args.L_0, True, None, "Armijo",
line_search, c1=c1, c2=c2)
start = time.time() - start
exp_res_dict['ArmijoAccDetGNM'][name][n][pair_num][line_search][i] = {'f_vals': f_vals,
'nabla_f_2_norm_vals': nabla_f_2_norm_vals,
'local_steps_list': local_steps_list,
'spec_steps_list': spec_steps_list,
'avg_time_s': start / len(f_vals),
'time_s': start}
del _, f_vals, nabla_f_2_norm_vals, local_steps_list, spec_steps_list, start
gc.collect()
if args.verbose:
print("Started ExtrapolationAccDetGNM!")
exp_res_dict['ExtrapolationAccDetGNM'] = dict()
for oracle_class, name in [(RosenbrockEvenSumOracle, 'Rosenbrock-Skokov'), (HatOracle, 'Hat')]:
if args.verbose:
print('Oracle:', name)
exp_res_dict['ExtrapolationAccDetGNM'][name] = dict()
for n in args.n_dims:
if args.verbose:
print(' n:', n)
exp_res_dict['ExtrapolationAccDetGNM'][name][n] = dict()
for line_search in ["None", "Armijo"]:
if args.verbose:
print(' line_search:', line_search)
exp_res_dict['ExtrapolationAccDetGNM'][name][n][line_search] = dict()
if line_search == "Armijo":
for probe_pair_num, (probe_c1, probe_c2) in enumerate(zip(args.c1_list, args.c2_list)):
if args.verbose:
print(' c1 = {:.4f}, c2 = {:.4f}:'.format(probe_c1, probe_c2))
exp_res_dict['ExtrapolationAccDetGNM'][name][n][line_search][probe_pair_num] = dict()
for i in range(args.n_starts):
if args.verbose:
print(' start #:', i + 1)
start = time.time()
_, f_vals, nabla_f_2_norm_vals, _, _, n_iter_list = AccDetGNM(oracle_class(n), args.N_iter, x_0_dict[n][i], args.L_0, True, None, "Extrapolation", line_search,
probe_c1=probe_c1, probe_c2=probe_c2)
start = time.time() - start
exp_res_dict['ExtrapolationAccDetGNM'][name][n][line_search][probe_pair_num][i] = {'f_vals': f_vals,
'nabla_f_2_norm_vals': nabla_f_2_norm_vals,
'n_iter_list': n_iter_list,
'avg_time_s': start / len(f_vals),
'time_s': start}
del _, f_vals, nabla_f_2_norm_vals, n_iter_list, start
gc.collect()
else:
for i in range(args.n_starts):
if args.verbose:
print(' start #:', i + 1)
start = time.time()
_, f_vals, nabla_f_2_norm_vals, _, _, n_iter_list = AccDetGNM(oracle_class(n), args.N_iter, x_0_dict[n][i], args.L_0, True, None, "Extrapolation", line_search)
start = time.time() - start
exp_res_dict['ExtrapolationAccDetGNM'][name][n][line_search][i] = {'f_vals': f_vals,
'nabla_f_2_norm_vals': nabla_f_2_norm_vals,
'n_iter_list': n_iter_list,
'avg_time_s': start / len(f_vals),
'time_s': start}
del _, f_vals, nabla_f_2_norm_vals, n_iter_list, start
gc.collect()
return exp_res_dict