def run_cnn( arch_params, optimization_params, dataset, filename_params, visual_params, n_epochs=200, validate_after_epochs=1, verbose=False, ): net = network(filename_params=filename_params, random_seed=arch_params["random_seed"], verbose=verbose) net.init_data(dataset, outs=arch_params["outs"], verbose=verbose) net.build_network(arch_params=arch_params, optimization_params=optimization_params, verbose=verbose) net.create_dirs(visual_params=visual_params) net.train(n_epochs=n_epochs, validate_after_epochs=validate_after_epochs, verbose=verbose) net.test(verbose=verbose) net.save_network() """
def run_cnn( arch_params, optimization_params , dataset, filename_params, visual_params, n_epochs = 200, validate_after_epochs = 1, verbose = False, ): net = network( filename_params = filename_params, random_seed = arch_params ["random_seed"], verbose = verbose ) net.init_data ( dataset, outs = arch_params["outs"], verbose = verbose ) net.build_network( arch_params = arch_params, optimization_params = optimization_params, verbose = verbose) net.create_dirs ( visual_params = visual_params ) net.train( n_epochs = n_epochs, validate_after_epochs = validate_after_epochs, verbose = verbose ) net.test( verbose = verbose ) net.save_network () """
def generality_experiment( arch_params, optimization_params , dataset, original_filename_params, filename_params_retrain, retrain_params, visual_params, validate_after_epochs = 1, n_epochs = 50, ft_epochs = 200, verbose = False ): params_loaded, arch_params_loaded = load_network (filename_params ["network_save_name"] , data_params = False, optimization_params = False) # retrain is used to do the dataset some wierd experiments. retrain_net = network( filename_params = filename_params_retrain, random_seed = arch_params ["random_seed"], verbose = verbose ) retrain_net.init_data ( dataset = dataset , outs = arch_params ["outs"], verbose = verbose ) retrain_net.build_network ( arch_params = arch_params_loaded, optimization_params = optimization_params, init_params = params_loaded, retrain_params = retrain_params, verbose = verbose ) retrain_net.create_dirs ( visual_params = visual_params ) retrain_net.train ( n_epochs = n_epochs, ft_epochs = ft_epochs, validate_after_epochs = validate_after_epochs, verbose = verbose) retrain_net.test ( verbose = verbose ) retrain_net.save_network ()