help='RAY Init num_cpus parameter.')
parser.add_argument('--ray-gpus',
default=0,
type=int,
help='RAY Init num_gpus parameter.')
######## Profiling
parser.add_argument('--profiler',
dest='profiler',
action='store_true',
help='Enables cProfile.')
parser.set_defaults(profiler=False)
return parser.parse_args()
ARGS = argument_parser()
logger = set_logging('runPPOtraining')
####################################################################################################
class NPEncoder(NumpyEncoder):
def default(self, obj):
try:
encoded_value = super(NPEncoder, self).default(obj)
return encoded_value
except:
logger.debug('%s ---> %s', str(type(obj)), str(obj))
return str(obj)
def load_json_file(json_file):
args = vars(parser.parse_args())
######################################
# Check Input
######################################
if not os.path.isfile(args['season_captures_csv']):
raise FileNotFoundError("season_captures_csv: {} not found".format(
args['season_captures_csv']))
if not os.path.isfile(args['predictions_csv']):
raise FileNotFoundError("predictions_csv: {} not found".format(
args['predictions_csv']))
# logging
set_logging(args['log_dir'], args['log_filename'])
logger = logging.getLogger(__name__)
for k, v in args.items():
logger.info("Argument {}: {}".format(k, v))
######################################
# Read Data
######################################
# read captures data
season_data_df = read_cleaned_season_file_df(args['season_captures_csv'])
n_images_in_season_data = season_data_df.shape[0]
logger.info("Read {} records from {}".format(n_images_in_season_data,
args['season_captures_csv']))
from utils.logger import set_logging
# """ Import SUMO library """
if 'SUMO_HOME' in os.environ:
sys.path.append(os.path.join(os.environ['SUMO_HOME'], 'tools'))
import traci
import libsumo
import traci.constants as tc
else:
sys.exit("please declare environment variable 'SUMO_HOME'")
####################################################################################################
DEBUGGER = True
logger = set_logging(__name__)
####################################################################################################
def env_creator(config):
""" Environment creator used in the environment registration. """
logger.debug(
'[env_creator] Environment creation: PrefChoiceRefCSPersuasiveDeepMARLEnv'
)
return PrefChoiceRefCSPersuasiveDeepMARLEnv(config)
####################################################################################################
'--action-distr',
type=float,
nargs='+',
help=
"Probability distribution for the epsilon action. Required with PDEGQLET."
)
parser.add_argument('--profiler',
dest='profiler',
action='store_true',
help='Enables cProfile.')
parser.set_defaults(profiler=False)
return parser.parse_args()
ARGS = argument_parser()
logger = set_logging('runA3Ctraining')
####################################################################################################
def load_json_file(json_file):
""" Loads a JSON file. """
logger.debug('Loading %s.', json_file)
return json.load(open(json_file))
####################################################################################################
CHECKPOINT_METRICS = [
# 'max_episode_reward_mean', # this is cumulative value
'min_policy_loss',
'--action-distr',
type=float,
nargs='+',
help=
"Probability distribution for the epsilon action. Required with PDEGQLET."
)
parser.add_argument('--profiler',
dest='profiler',
action='store_true',
help='Enables cProfile.')
parser.set_defaults(profiler=False)
return parser.parse_args()
ARGS = argument_parser()
logger = set_logging('runDQNtraining')
####################################################################################################
class NPEncoder(NumpyEncoder):
def default(self, obj):
try:
encoded_value = super(NPEncoder, self).default(obj)
return encoded_value
except:
logger.debug('%s ---> %s', str(type(obj)), str(obj))
return str(obj)
def load_json_file(json_file):
parser.add_argument("--images_to_match_path", type=str, required=True)
parser.add_argument("--output_csv", type=str, default=None)
args = vars(parser.parse_args())
# Check Input
if not os.path.isfile(args['captures']):
raise FileNotFoundError("captures: {} not found".format(
args['captures']))
if not os.path.isdir(args['images_to_match_path']):
raise FileNotFoundError(
"images_to_match_path: {} must be a directory".format(
args['images_to_match_path']))
# logging
set_logging()
# find all images
images_to_find = list_pictures(args['images_to_match_path'],
ext=('jpg', 'jpeg'))
logger.info("Found {} images in {}".format(len(images_to_find),
args['images_to_match_path']))
captures = read_image_inventory(args['captures_csv'],
unique_id='image_path')
logger.info("Read {} with {} images".format(args['captures_csv'],
len(captures.keys())))
images_to_search_in = list(captures.keys())
