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import numpy as np
from keras.models import Sequential
from keras.layers import Dense, Activation, Embedding, TimeDistributedMerge
from keras.optimizers import SGD
from keras.utils import np_utils

def load_data(path):
    id2word = []
    word2id = {}
    with open(path) as f:

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*.aux
*.bbl
*.dvi
*.blg
*.fdb_latexmk
*.fls
*.log
*.synctex.gz
*.toc
*.lot

nzw0301

# coding: utf-8

import sys
import math
import numpy as np
from sklearn.feature_extraction.text import CountVectorizer
from sklearn import preprocessing
import scipy.special

fname = sys.argv[1]

nzw0301

# coding: utf-8

import numpy as np
import sys
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.cross_validation import train_test_split

def logistic_function(mat):
    return 1/(1+np.exp(-mat))

nzw0301

# coding: utf-8

import numpy as np
import sys
from sklearn.feature_extraction.text import CountVectorizer


def logistic_function(mat):
    return 1/(1+np.exp(-mat))