def main():
parser = argparse.ArgumentParser()
parser.add_argument("-v", "--verbosity", help="increase output verbosity", action="count")
parser.add_argument("-q", "--quiet", help="supress output (except errors)", action="store_true")
parser.add_argument("--device-type", help="device type (all, gpu or cpu), default is all", type=str, default='all')
parser.add_argument("--no-save", help="skip saving best fitness simulation", action="store_true")
parser.add_argument("-w", "--inertia", help="set PSO inertia (W) parameter, default is 0.9", type=float, default=0.9)
parser.add_argument("-a", "--alfa", help="set PSO alfa parameter, default is 2.0", type=float, default=2)
parser.add_argument("-b", "--beta", help="set PSO beta parameter, default is 2.0", type=float, default=2)
parser.add_argument("--ta", help="number of timesteps without fitness avaliation, default is 600", type=int, default=600)
parser.add_argument("--tb", help="number of timesteps with fitness avaliation, default is 5400", type=int, default=5400)
parser.add_argument("-g", "--num-generations", help="number of generations, default is 500", type=int, default=500)
parser.add_argument("-r", "--num-runs", help="number of runs, default is 3", type=int, default=3)
parser.add_argument("-n", "--num-robots", help="number of robots, default is 10", type=int, default=10)
parser.add_argument("-p", "--population-size", help="PSO population size (particles), default is 10", type=int, default=10)
parser.add_argument("--targets-distances", help="list of distances between target areas to be evaluated \
each generation, default is 0.7 0.9 1.1 1.3 1.5", type=float, nargs='+', default=[0.7, 0.9, 1.1, 1.3, 1.5])
parser.add_argument("--targets-angles", help="list of axis angles where the target areas \
are located each trial (between 0 and PI), default is [3*pi/4]", type=float, nargs='+', default=[2.356194490192345])
parser.add_argument("--random-targets", help="place targets at random position (obeying targets distances)", action="store_true")
parser.add_argument("--symetrical-targets", help="place targets at symetrical position", action="store_true")
parser.add_argument("-t", "--trials", help="number of trials per distance, default is 3", type=int, default=3)
args = parser.parse_args()
if args.verbosity >= 2:
__log__.setLevel(logging.DEBUG)
elif args.verbosity == 1:
__log__.setLevel(logging.INFO)
else:
__log__.setLevel(logging.WARNING)
if args.quiet:
__log__.setLevel(logging.ERROR)
uri = os.environ.get('SOLACE_URI')
username = os.environ.get('SOLACE_USERNAME')
password = os.environ.get('SOLACE_PASSWORD')
try:
git_version = subprocess.check_output('git describe --tags --long'.split(), stderr=subprocess.STDOUT).replace('\n', '')
except:
git_version = None
if (uri is None) or (username is None) or (password is None):
raise Exception('Environment variables (SOLACE_URI, SOLACE_USERNAME, SOLACE_PASSWORD) not set!')
device_type = cl.device_type.ALL
if args.device_type == 'cpu':
device_type = cl.device_type.CPU
elif args.device_type == 'gpu':
device_type = cl.device_type.GPU
platform = cl.get_platforms()[0]
devices = platform.get_devices(device_type=device_type)
context = cl.Context(devices=devices)
queue = cl.CommandQueue(context)
exp = solace.get_experiment(uri, username, password)
inst = exp.create_instance(args.num_runs, {
'W': args.inertia,
'ALFA': args.alfa,
'BETA': args.beta,
'STEPS_TA': args.ta,
'STEPS_TB': args.tb,
'NUM_GENERATIONS': args.num_generations,
'NUM_RUNS': args.num_runs,
'NUM_ROBOTS': args.num_robots,
'POPULATION_SIZE': args.population_size,
'TARGETS_DISTANCES': args.targets_distances,
'TARGETS_ANGLES': args.targets_angles,
'TRIALS': args.trials,
'RANDOM_TARGETS': 1 if args.random_targets else 0,
'SYMETRICAL_TARGETS': 1 if args.symetrical_targets else 0
}, code_version=git_version)
for run in inst.runs:
DiscretePSO(context, queue).execute(run, args)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("-v", "--verbosity", help="increase output verbosity", action="count")
parser.add_argument("-q", "--quiet", help="supress output (except errors)", action="store_true")
parser.add_argument("--device-type", help="device type (all, gpu or cpu), default is all", type=str, default="all")
parser.add_argument("--islands-per-device", help="number of islands per device, default is 1", type=int, default=1)
parser.add_argument("--no-save", help="skip saving best fitness simulation", action="store_true")
parser.add_argument(
"--ta", help="number of timesteps without fitness avaliation, default is 600", type=int, default=600
)
parser.add_argument(
"--tb", help="number of timesteps with fitness avaliation, default is 5400", type=int, default=5400
)
parser.add_argument("-g", "--num-generations", help="number of generations, default is 500", type=int, default=500)
parser.add_argument("-r", "--num-runs", help="number of runs, default is 3", type=int, default=3)
parser.add_argument("-n", "--num-robots", help="number of robots, default is 10", type=int, default=10)
parser.add_argument(
"-p", "--population-size", help="population size (genomes), default is 120", type=int, default=120
)
parser.add_argument(
"--targets-distances",
help="list of distances between target areas to be evaluated \
each generation, default is 0.7 0.9 1.1 1.3 1.5",
type=float,
nargs="+",
default=[0.7, 0.9, 1.1, 1.3, 1.5],
)
parser.add_argument(
"--targets-angles",
help="list of axis angles where the target areas \
are located each trial (between 0 and PI), default is [3*pi/4]",
type=float,
nargs="+",
default=[2.356194490192345],
)
parser.add_argument(
"--random-targets", help="place targets at random position (obeying targets distances)", action="store_true"
)
parser.add_argument("--symetrical-targets", help="place targets at symetrical position", action="store_true")
parser.add_argument("-t", "--trials", help="number of trials per distance, default is 3", type=int, default=3)
parser.add_argument("-c", "--pcrossover", help="probability of crossover, default is 0.9", type=float, default=0.9)
parser.add_argument("-m", "--pmutation", help="probability of mutation, default is 0.03", type=float, default=0.03)
parser.add_argument(
"-o",
"--offspring",
help="number of children each couple of indivuals generate, MUST BE EVEN, default is 6",
type=int,
default=6,
)
parser.add_argument("-e", "--elite-size", help="size of population elite, default is 24", type=int, default=24)
parser.add_argument(
"--migration-rate",
help="proportion of individual of a population that migrate, default is 0.1",
type=float,
default=0.1,
)
parser.add_argument(
"--migration-freq", help="frequency of migration (in generations), default is 10", type=int, default=10
)
args = parser.parse_args()
if args.verbosity >= 2:
__log__.setLevel(logging.DEBUG)
elif args.verbosity == 1:
__log__.setLevel(logging.INFO)
else:
__log__.setLevel(logging.WARNING)
if args.quiet:
__log__.setLevel(logging.ERROR)
if (args.offspring % 2) != 0:
__log__.error("Offspring must be an even number!")
sys.exit(1)
uri = os.environ.get("SOLACE_URI")
username = os.environ.get("SOLACE_USERNAME")
password = os.environ.get("SOLACE_PASSWORD")
try:
git_version = subprocess.check_output("git describe --tags --long".split(), stderr=subprocess.STDOUT).replace(
"\n", ""
)
except:
git_version = None
if (uri is None) or (username is None) or (password is None):
raise Exception("Environment variables (SOLACE_URI, SOLACE_USERNAME, SOLACE_PASSWORD) not set!")
device_type = cl.device_type.ALL
if args.device_type == "cpu":
device_type = cl.device_type.CPU
elif args.device_type == "gpu":
device_type = cl.device_type.GPU
platform = cl.get_platforms()[0]
devices = platform.get_devices(device_type=device_type)
context = cl.Context(devices=devices)
exp = solace.get_experiment(uri, username, password)
inst = exp.create_instance(
args.num_runs,
{
"PCROSSOVER": args.pcrossover,
"PMUTATION": args.pmutation,
"ELITE_SIZE": args.elite_size,
"OFFSPRING": args.offspring,
"MIGRATION_RATE": args.migration_rate,
"MIGRATION_FREQ": args.migration_freq,
"STEPS_TA": args.ta,
"STEPS_TB": args.tb,
"NUM_GENERATIONS": args.num_generations,
"NUM_RUNS": args.num_runs,
"NUM_ROBOTS": args.num_robots,
"POPULATION_SIZE": args.population_size,
"TARGETS_DISTANCES": args.targets_distances,
"TARGETS_ANGLES": args.targets_angles,
"TRIALS": args.trials,
"RANDOM_TARGETS": 1 if args.random_targets else 0,
"SYMETRICAL_TARGETS": 1 if args.symetrical_targets else 0,
},
code_version=git_version,
)
for run in inst.runs:
PGA(context, args).execute(run)
PARAM1 = 5.3
PARAM2 = [ 5, 4, 2 ]
PARAM3 = False
PARAM4 = 'fox'
PARAM5 = {'foo': 'bar', 'list': [3, 2, 1]}
def step(var1, var2):
var1 += random.uniform(0,1)
var2 += random.uniform(0,1.5)
time.sleep(5)
return var1, var2
if __name__=="__main__":
exp = solace.get_experiment('solace://lys:3000/test', 'admin', 'a0358070')
inst = exp.create_instance(NUM_RUNS, {'PARAM1': PARAM1, 'PARAM2': PARAM2, 'PARAM3': PARAM3, 'PARAM4': PARAM4, 'PARAM5': PARAM5, 'NUM_STEPS': NUM_STEPS})
for run in inst.runs:
run.begin()
# the variables we are optimizing (just as an example)
var1 = 0
var2 = 0
current_step = 0
while current_step < NUM_STEPS:
var1, var2 = step(var1, var2)
current_step += 1
run.progress(current_step / float(NUM_STEPS), {'var1': var1, 'var2': var2})
PARAM3 = False
PARAM4 = 'fox'
PARAM5 = {'foo': 'bar', 'list': [3, 2, 1]}
def step(var1, var2):
var1 += random.uniform(0, 1)
var2 += random.uniform(0, 1.5)
time.sleep(5)
return var1, var2
if __name__ == "__main__":
exp = solace.get_experiment('solace://lys:3000/test', 'admin', 'a0358070')
inst = exp.create_instance(
NUM_RUNS, {
'PARAM1': PARAM1,
'PARAM2': PARAM2,
'PARAM3': PARAM3,
'PARAM4': PARAM4,
'PARAM5': PARAM5,
'NUM_STEPS': NUM_STEPS
})
for run in inst.runs:
run.begin()
# the variables we are optimizing (just as an example)
var1 = 0