~/data
~/data/A/A (1).jpg
~/data/A/A (2).jpg
...
~/data/Z/Z (1).jpg
~/data/Z/Z (2).jpg
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import os | |
import csv | |
import itertools | |
import functools | |
import tensorflow as tf | |
import numpy as np | |
import array | |
tf.flags.DEFINE_integer( | |
"min_word_frequency", 5, "Minimum frequency of words in the vocabulary") |
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consumer_key='' | |
consumer_secret ='' | |
access_token = '' | |
access_token_secret = '" |
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consumer_key = ' ' | |
consumer_secret = ' ' | |
access_token = ' ' | |
access_token_secret = ' ' |
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import numpy as np | |
import sys | |
class RecurrentNeuralNetwork: | |
def __init__(self,xs,ys,rl,eo,lr): | |
self.x=np.zeros(xs) | |
self.xs=xs | |
self.y=np.zeros(ys) | |
self.ys=ys | |
self.w=np.random.random((ys,ys)) |
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import sys,random,time | |
alpha=('a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','s','t','u','v','w','x','y','z') | |
words="" | |
starttime =time.time() | |
#monkey iterator | |
while str(sys.argv[1]) not in words : | |
a=random.choice(alpha) | |
words+=a | |
print words |