def tune_args(args): """ tune the dataset specific args so train_file or test_file need not be changed """ try: files = dataset_files_pairs.get(args.dataset) args.data_root, args.train_file, args.valid_file, args.test_file = files return args except AssertionError: err("Error. Cannot find the specific key -> {} in dataset_files_pairs.".format(args.dataset))
def make_sure_model_is_valid(self): """ check if the model has necessary attributes """ try: _ = self.loss _ = self.correct_prediction except AttributeError as e: err("Your model {} doesn't have enough attributes.\nError Message:\n\t{}" .format(self.model_name, e)) self.sess.close() exit(1)
def confirm_model_dataset_fitness(self): # make sure the models_in_datasets var is correct try: assert (models_in_datasets.get(self.args.dataset, None) is not None) except AssertionError: err("Models_in_datasets doesn't have the specified dataset key: {}." .format(self.args.dataset)) self.sess.close() exit(1) # make sure the model fit the dataset try: assert (self.model_name in models_in_datasets.get(self.args.dataset, None)) except AssertionError: err("The model -> {} doesn't support the dataset -> {}".format( self.model_name, self.args.dataset)) self.sess.close() exit(1)