<s> import os <EOL> from model_comparison import * <EOL> import argparse <EOL> if __name__ == '<STR_LIT:__main__>' : <EOL> usage = '<STR_LIT>' <EOL> parser = argparse . ArgumentParser ( usage = usage ) <EOL> parser . add_argument ( '<STR_LIT>' ) <EOL> parser . add_argument ( '<STR_LIT>' , dest = '<STR_LIT:test>' , action = '<STR_LIT:store_true>' , default = False ) <EOL> parser . add_argument ( '<STR_LIT>' , dest = '<STR_LIT>' , action = '<STR_LIT:store>' , type = int , default = <NUM_LIT:1> ) <EOL> parser . add_argument ( '<STR_LIT>' , dest = '<STR_LIT>' , action = '<STR_LIT:store>' , type = str , default = '<STR_LIT>' ) <EOL> parser . add_argument ( '<STR_LIT>' , dest = '<STR_LIT>' , action = '<STR_LIT:store>' , type = int , default = <NUM_LIT:3> ) <EOL> parser . add_argument ( '<STR_LIT>' , dest = '<STR_LIT>' , action = '<STR_LIT:store>' , type = float , default = <NUM_LIT:0.1> ) <EOL> parser . add_argument ( '<STR_LIT>' , dest = '<STR_LIT>' , action = '<STR_LIT:store>' , type = int , default = <NUM_LIT:3> ) <EOL> parser . add_argument ( '<STR_LIT>' , dest = '<STR_LIT>' , action = '<STR_LIT:store>' , type = int , default = <NUM_LIT:100> ) <EOL> parser . add_argument ( '<STR_LIT>' , dest = '<STR_LIT>' , action = '<STR_LIT:store_true>' , default = False ) <EOL> parser . add_argument ( '<STR_LIT>' , dest = '<STR_LIT>' , action = '<STR_LIT:store>' , type = str , default = '<STR_LIT>' ) <EOL> parser . add_argument ( '<STR_LIT>' , dest = '<STR_LIT>' , action = '<STR_LIT:store>' , type = str , default = None ) <EOL> options = parser . parse_args ( ) <EOL> cur_dir = os . getcwd ( ) <EOL> abspath = os . path . abspath ( __file__ ) <EOL> dname = os . path . dirname ( abspath ) <EOL> os . chdir ( dname ) <EOL> with open ( options . output_dir + '<STR_LIT>' , '<STR_LIT:rb>' ) as f : <EOL> learn_options = pickle . load ( f ) <EOL> results , all_learn_options = run_models ( [ options . model ] , learn_options_set = learn_options , orders = [ options . order ] , test = options . test , <EOL> GP_likelihoods = [ options . likelihood ] , WD_kernel_degrees = [ options . WD ] , <EOL> adaboost_num_estimators = [ options . adaboost_num_estimators ] , <EOL> adaboost_max_depths = [ options . adaboost_max_depth ] , adaboost_learning_rates = [ options . adaboost_lr ] , <EOL> adaboost_CV = options . adaboost_CV ) <EOL> if options . exp_name is None : <EOL> exp_name = results . keys ( ) [ <NUM_LIT:0> ] <EOL> else : <EOL> exp_name = results . keys ( ) [ <NUM_LIT:0> ] <EOL> os . chdir ( cur_dir ) <EOL> with open ( options . output_dir + '<STR_LIT:/>' + exp_name + '<STR_LIT>' , '<STR_LIT:wb>' ) as f : <EOL> pickle . dump ( ( results , all_learn_options ) , f ) </s>
