settings_.gradient_penalty_multiplier = 1e2 settings_.map_directory_name = ['density3e-1'] settings_.map_multiplier = 1e-3 else: raise ValueError(f'{application_name} is not an available application.') settings_.summary_step_period = 5000 settings_.labeled_dataset_seed = 0 settings_.steps_to_run = 100000 settings_.learning_rate = [1e-4] # settings.load_model_path = 'logs/k comparison i1nn_maps ShanghaiTech crowd dnn ul1e3 fl1e2 gp1e2 lr1e-4 mm1e-6 ls0 bs40' settings_.contrasting_distance_function = abs_plus_one_sqrt_mean_neg settings_.matching_distance_function = abs_mean settings_.continue_existing_experiments = False settings_.save_step_period = 20000 settings_.local_setup() settings_list = convert_to_settings_list(settings_, shuffle=True) seed_all(0) previous_trial_directory = None for settings_ in settings_list: trial_name = f'base' trial_name += f' {settings_.matching_distance_function.__name__} {settings_.contrasting_distance_function.__name__}' trial_name += f' {method_name.value}' if method_name != MethodName.srgan else '' trial_name += f' {application_name.value}' trial_name += f' {settings_.map_directory_name}' if application_name == ApplicationName.crowd else '' trial_name += f' {settings_.crowd_dataset.value}' if application_name == ApplicationName.crowd else '' if method_name != MethodName.dnn: if application_name == ApplicationName.crowd and settings_.crowd_dataset == CrowdDataset.world_expo: trial_name += f' c{settings_.number_of_cameras}i{settings_.number_of_images_per_camera}' else: trial_name += f' le{settings_.labeled_dataset_size}' trial_name += f' ue{settings_.unlabeled_dataset_size}'
raise ValueError( '{} is not an available application.'.format(application_name)) settings_.unlabeled_dataset_size = [50000] settings_.labeled_dataset_size = [1000] settings_.summary_step_period = 1000 settings_.labeled_dataset_seed = [0] settings_.steps_to_run = 1000000 settings_.learning_rate = [1e-4] settings_.gradient_penalty_multiplier = [0] settings_.mean_offset = [0] settings_.unlabeled_loss_order = 2 settings_.fake_loss_order = 0.5 settings_.generator_loss_order = 2 settings_.load_model_path = '/home/golmschenk/srgan/logs/spp shanghai al crowd c5i5 ul1e0 fl1e0 gp0e0 mo0e0 lr1e-4 gs1 ls0 u2f0.5g2 bs100' settings_.local_setup() settings_list = convert_to_settings_list(settings_) seed_all(0) for settings_ in settings_list: trial_name = 'spp shanghai al' trial_name += ' {}'.format(application_name) trial_name += ' {}'.format(method_name) if method_name != 'srgan' else '' if application_name == 'crowd': trial_name += ' c{}i{}'.format(settings_.number_of_cameras, settings_.number_of_images_per_camera) else: trial_name += ' le{}'.format(settings_.labeled_dataset_size) trial_name += ' ue{}'.format(settings_.unlabeled_dataset_size) trial_name += ' ul{:e}'.format(settings_.unlabeled_loss_multiplier) trial_name += ' fl{:e}'.format(settings_.fake_loss_multiplier) trial_name += ' gp{:e}'.format(settings_.gradient_penalty_multiplier) trial_name += ' mo{:e}'.format(settings_.mean_offset)