def e_008(): a = ProjectVariable() a.experiment_name = '008. caviar, cosine, no CLR, rank=36' a.ranking_number = 36 a.iterations = 10 a.datasets = ['caviar'] a.cost_module_type = 'cosine' a.use_cyclical_learning_rate = False a.log_file = 'thesis_experiment_log.txt' scn.super_main(a)
def e_079(): a = ProjectVariable() a.experiment_name = '079. prid450: selu + alphadropout=0.05 + no batchnorm' a.ranking_number = 100 a.iterations = 30 a.activation_function = 'selu' a.datasets = ['prid450'] a.log_file = 'thesis_experiment_log.txt' a.head_type = 'simple' a.dropout_rate = 0.05 scn.super_main(a)
def e_057(): a = ProjectVariable() a.experiment_name = '057. viper: selu + alphadropout=0.1 + no batchnorm' a.ranking_number = 100 a.iterations = 10 a.activation_function = 'selu' a.datasets = ['viper'] a.log_file = 'thesis_experiment_log.txt' a.head_type = 'simple' a.dropout_rate = 0.1 scn.super_main(a)
def e_073(): a = ProjectVariable() a.experiment_name = '073. priming on viper. no CLR. LR = 0.00000001' a.log_file = 'thesis_experiment_log.txt' a.priming = True a.ranking_number = 316 a.load_weights_name = 'viper_weigths_0.h5' a.datasets = ['viper'] a.prime_epochs = 5 a.use_cyclical_learning_rate = False a.learning_rate = 0.00000001 a.iterations = 10 prime.super_main(a)
def e_074(): a = ProjectVariable() a.experiment_name = '074. pretend save viper for priming' a.epochs = 100 # a.save_inbetween = True # a.name_indication = 'dataset_name' # a.save_points = [100] a.ranking_number = 316 a.iterations = 1 a.activation_function = 'elu' a.neural_distance = 'absolute' a.datasets = ['viper'] a.log_file = 'thesis_experiment_log.txt' scn.super_main(a)
def e_034(): a = ProjectVariable() a.experiment_name = '034. cnn_lstm on prid2011, AD=0.1' a.epochs = 100 a.iterations = 1 a.batch_size = 32 a.activation_function = 'selu' a.datasets = ['prid2011'] a.video_head_type = 'cnn_lstm' a.sequence_length = 20 a.ranking_number = 30 a.dropout_rate = 0.1 a.lstm_units = 64 srcn.super_main(a)
def e_032(): a = ProjectVariable() a.experiment_name = '032. 3D convolutions on prid2011' a.epochs = 100 a.iterations = 1 a.batch_size = 32 a.activation_function = 'elu' a.datasets = ['prid2011'] a.video_head_type = '3d_convolution' a.sequence_length = 20 a.kernel = (3, 3, 3) a.pooling_size = [[1, 4, 2], [1, 2, 2]] a.ranking_number = 30 srcn.super_main(a)
def e_039(): a = ProjectVariable() a.experiment_name = '039. save cuhk02 for priming' a.epochs = 100 a.save_inbetween = True a.name_indication = 'dataset_name' a.save_points = [100] a.ranking_number = 100 a.iterations = 1 a.batch_size = 32 a.activation_function = 'elu' a.cl_min = 0.00005 a.cl_max = 0.001 a.neural_distance = 'absolute' a.datasets = ['cuhk02'] a.log_file = 'thesis_experiment_log.txt' scn.super_main(a)
def e_092(): a = ProjectVariable() a.experiment_name = '092. viper > grid' a.epochs = 100 # a.save_inbetween = True # a.name_indication = 'dataset_name' # a.save_points = [100] a.ranking_number = 125 a.iterations = 10 a.batch_size = 32 a.load_weights_name = 'viper_weigths_base.h5' a.activation_function = 'elu' a.cl_min = 0.00005 a.cl_max = 0.001 a.neural_distance = 'absolute' a.datasets = ['grid'] a.log_file = 'thesis_experiment_log.txt' scn.super_main(a)