mp = maps[chosen_map] # Chooses map for generation # Simulator config.load_simulator = sim_start config.simulator_graphics = False config.simulator_initial_map = mp config.simulator_algorithm_type, config.simulator_testing_type, config.simulator_algorithm_parameters = algo config.simulator_key_frame_speed, config.simulator_key_frame_skip = ani config.simulator_write_debug_level = debug # These are for training config.generator_labelling_features = labelling[training_algo][0] config.generator_labelling_labels = labelling[training_algo][1] config.generator_single_labelling_features = labelling[training_algo][2] config.generator_single_labelling_labels = labelling[training_algo][3] config.generator_aug_labelling_features = [] config.generator_aug_labelling_labels = [] config.generator_aug_single_labelling_features = [] config.generator_aug_single_labelling_labels = [] config.generator_modify = None config.generator_show_gen_sample = show_sample_map config.generator_nr_of_examples = nbr_ex if args.full_train: config.generator = True for m in gen_maps.values(): config.generator_gen_type = m config.generator_labelling_atlases = [m + '_' + str(nbr_ex)]
if config.generator_house_expo: gen_map = '_house_expo' config.generator_labelling_atlases = [gen_map] config.generator_nr_of_examples = nbr_ex else: gen_map = gen_maps[chosen_map] config.generator_labelling_atlases = [gen_map + '_' + str(nbr_ex)] config.generator_nr_of_examples = nbr_ex config.generator_gen_type = gen_map #These are for training config.generator_labelling_features = [] config.generator_labelling_labels = [] config.generator_single_labelling_features = [] config.generator_single_labelling_labels = [] config.generator_aug_labelling_features = [] config.generator_aug_labelling_labels = [] config.generator_aug_single_labelling_features = [] config.generator_aug_single_labelling_labels = [] config.generator_modify = None config.generator_show_gen_sample = show_sample_map #Trainer config.trainer = train_start # config.trainer_model = training_algo #Either BasicLSTMModule or CAE or LSTMCAEModel # config.trainer_custom_config = { # "local_kernel": (AStar, ([], {})), # "global_kernel": (CombinedOnlineLSTM, ([], {})), "global_kernel_max_it": 100 # }