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())