def create_npc(loc, gender, level, mood): """ Create NPC Args: loc (int): Location gender (string): gender level (int): NPC level mood (int): NPC mood Returns: class: NPC """ if gen_names == "neuro": name = get_name(gender) else: name = random_name(gender) return NPC(name, gender, level, loc, mood)
def create_name(): """Create Babka's name if no name is specified, the function will generate a random name. Returns: string: Generated Babka's name """ menu.print_title('Создание бабки') print('Если имя не будет введено, то будет сгенерировано случайное имя.') name = input('Введи имя: ') if not name: print('Хорошо, я сгенерирую рандомное имя для бабки...') if gen_names == "neuro": name = get_name('female') else: name = random_name('female') print('Имя бабки: ', name) return name elif is_string(name): print("Хорошо!") return name
def main(): while True: answer = input("Do you want to generate another character? y/n \n") if answer == 'y': generating() print_out() re_roll() print(my_char) name = get_name() print(name) print(str(my_char) + "\n") strn, dext, cons, wisd, inte, cha_ism = lets_go() print(f"{strn} \n\n") with open("char.txt", "a+") as file: file.write(name + "\n") file.write(str(my_char) + "\n") file.write(str() + "\n\n") elif answer == 'n': print("See you later, stranger") break else: print("The input should be 'y' or 'n' \n")
import tensorflow as tf import numpy as np import pandas as pd import functools import datetime import os import name_gen as ng import gensim np.random.seed(1000) DTYPE = 'float32' RUN_NAME = ng.get_name() LOG_DIR = '/home/xuri3814/data/clickbait/cnn/runs/logs/{}/'.format(RUN_NAME) CHECKPOINT_DIR = '/home/xuri3814/data/clickbait/cnn/runs/checkpoints/{}/'.format(RUN_NAME) DATA_DIR = '/home/xuri3814/data/clickbait/' import os os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID" # see issue #152 os.environ["CUDA_VISIBLE_DEVICES"] = "0" def lazy_property(function): """ http://danijar.com/structuring-your-tensorflow-models/ http://www.wildml.com/2015/12/implementing-a-cnn-for-text-classification-in-tensorflow/ paper: http://arxiv.org/abs/1408.5882 :param function: :return: """ attribute = '_cache_' + function.__name__