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__