def test_parse_dispatcher_config(self):
raw_strings = [
# true flag
({
'true_flag': [True]
}, [" --true_flag"]),
# flase flag
({
'false_flag': [False]
}, [""]),
# flase flag followed by true flag
({
'false_flag': [False],
'true_flag': [True]
}, [" --true_flag"]),
# Different options
({
'flag': ["opt1", "opt2"]
}, [" --flag opt1", " --flag opt2"]),
# val
({
"val_flag": [5]
}, [" --val_flag 5"]),
# list of vals
({
"list_flag": [['t1/a=v', 't2/b=w']]
}, [" --list_flag t1/a=v t2/b=w"])
]
for config, expected in raw_strings:
wrapped_config = {"search_space": config}
output, _ = parsing.parse_dispatcher_config(wrapped_config)
self.assertCountEqual(output, expected)
def test_experimental_axies(self):
raw_strings = [
({
'experimented_flag': [True, False],
'const_flag': [False]
}, "experimented_flag"),
]
for config, expected in raw_strings:
wrapped_config = {"search_space": config}
_, output = parsing.parse_dispatcher_config(wrapped_config)
self.assertEqual(output[0], expected)
def test_invalid_config(self):
raw_strings = [
({
'flag1': [True, False],
'flag2': []
}, 'flag2'),
({
'flag1': []
}, 'flag1'),
({
'flag1': [True],
'flag2': "value",
}, 'flag2'),
]
for config, flag in raw_strings:
wrapped_config = {"search_space": config}
with self.assertRaises(Exception) as context:
parsing.parse_dispatcher_config(wrapped_config)
self.assertTrue(
self.err_msg.format(flag,
config[flag]) in str(context.exception))
if __name__ == "__main__":
args = parser.parse_args()
if not os.path.exists(args.experiment_config_path):
print(
CONFIG_NOT_FOUND_MSG.format("experiment",
args.experiment_config_path))
sys.exit(1)
experiment_config = json.load(open(args.experiment_config_path, 'r'))
if 'results_path' in experiment_config['search_space']:
print(RESULTS_PATH_APPEAR_ERR)
sys.exit(1)
job_list, experiment_axies = parsing.parse_dispatcher_config(
experiment_config)
job_queue = multiprocessing.Queue()
done_queue = multiprocessing.Queue()
for job in job_list:
job_queue.put(job)
print("Launching Dispatcher with {} jobs!".format(len(job_list)))
print()
for gpu in experiment_config['available_gpus']:
print("Start gpu worker {}".format(gpu))
multiprocessing.Process(target=worker,
args=(gpu, job_queue, done_queue)).start()
print()
summary = []
result_keys = []