Esempio n. 1
0
#!/usr/bin/env python
#!/usr/bin/env python
'''
This server manages a queue, which is shared by the workers and
the autoscaler. It also generates tokens. The queue is on port
6200.
'''

import remotequeue
from bottle import route, response, run, request
import random

# set up queue manager
AUTH_KEY = 'changeinprod'
MANAGED_QUEUE = remotequeue.make(AUTH_KEY, public=True)

# constants
LETTERS = 'abcefghijklmnopqrstuvwxyz'
URL_CACHE = {}


def url_test(url):
    ''' tests to see if the str passed is a fb profile image url'''
    # needs significant testing!
    if 'http' not in url:
        return False
    return 'facebook' in url.lower() or 'fb' in url.lower()


def generate_token():
    ''' returns string len 24 of lowercase letters '''
Esempio n. 2
0
# make sure to drop this file in the char-rnn directory
# creates a pool of words, and adds to the pool when it starts getting too small

import traceback
import remotequeue
import time
import rnn
import pronounce
import random

Q = remotequeue.make('secret', False)
amazing_models = open('amazing_models').read().splitlines()

def sample_model(model, chars = 5000):
    try:
        model_path = model.split(';')[0].strip()
        temp = model.split(';')[1].strip()
        words = rnn.run_temperature(model_path, temp, chars).splitlines()[2:-2]
        print model,'generated',len(words)
        return words
    except:
        print traceback.format_exc()
        return []

def create_words(num):
    print 'creating',num,'words'
    pool = set()
    while len(pool) < num * 1.5:
        model = random.choice(amazing_models)
        print 'sampling from model',model
        for word in sample_model(model):