def configurate_outputs()

in ModelConf.py [0:0]

• 42 lines of code
• 20 McCabe index (conditional complexity)

    def configurate_outputs(self):
        def configurate_logger(self):
            if self.phase == 'cache':
                return

            # dir
            if hasattr(self.params, 'log_dir') and self.params.log_dir:
                self.log_dir = self.params.log_dir
                prepare_dir(self.log_dir, True, allow_overwrite=True)
            else:
                self.log_dir = self.save_base_dir
            
            # path
            self.train_log_path = os.path.join(self.log_dir, self.train_log_name)
            self.test_log_path = os.path.join(self.log_dir, self.test_log_name)
            self.predict_log_path = os.path.join(self.log_dir, self.predict_log_name)
            if self.phase == 'train':
                log_path = self.train_log_path
            elif self.phase == 'test':
                log_path = self.test_log_path
            elif self.phase == 'predict':
                log_path =  self.predict_log_path
            if log_path is None:
                self.raise_configuration_error(self.phase + '_log_name')

            # log level
            if self.mode == 'philly' or self.params.debug:
                log_set(log_path, console_level='DEBUG', console_detailed=True, disable_log_file=self.params.disable_log_file)
            else:
                log_set(log_path, disable_log_file=self.params.disable_log_file)

        # save base dir
        if hasattr(self.params, 'model_save_dir') and self.params.model_save_dir:
            self.save_base_dir = self.params.model_save_dir
        elif self.save_base_dir is None:
            self.raise_configuration_error('save_base_dir')

        # prepare save base dir 
        if self.phase != 'cache':
            prepare_dir(self.save_base_dir, True, allow_overwrite=self.params.force or self.mode == 'philly',
                        extra_info='will overwrite model file and train.log' if self.phase=='train' else 'will add %s.log and predict file'%self.phase)

        # logger
        configurate_logger(self)

        # predict output path
        if self.phase != 'cache':
            if self.params.predict_output_path:
                self.predict_output_path = self.params.predict_output_path
            else:
                self.predict_output_path = os.path.join(self.save_base_dir, self.predict_output_name)
            logging.debug('Prepare dir for: %s' % self.predict_output_path)
            prepare_dir(self.predict_output_path, False, allow_overwrite=self.params.force or self.mode == 'philly')

        if self.predict_fields is None:
            self.predict_fields = DefaultPredictionFields[ProblemTypes[self.problem_type]]

        self.model_save_path = os.path.join(self.save_base_dir, self.model_name)