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)