Pasties 2016-12-18 17:06:56 +0000

import numpy as np
np.random.seed(1337)

import keras
from keras.models import Sequential
from keras.layers import Dense, LSTM, TimeDistributed
from keras.utils import np_utils
from tqdm import tqdm

import random
random.seed(1)


def generate():
    X = np.array([[random.choice([0, 1]) for _ in range(n)]
                  for _ in range(batch)])
    Y = np.concatenate(([[0] * n], X[:-1]))
    X = X.reshape(batch, 1, n)
    Y = Y.reshape(batch, 1, n)
    return X, Y


n = 1

model = Sequential()
model.add(LSTM(n + max(n, 5), input_shape=(1, n), return_sequences=True))
model.add(TimeDistributed(Dense(n, activation='sigmoid')))
model.compile(loss='binary_crossentropy', optimizer='adam',
              metrics=['binary_accuracy'])


for i in tqdm(range(20)):
    batch = 30
    X, Y = generate()
    model.fit(X, Y, nb_epoch=30, batch_size=batch, shuffle=False, verbose=0)

for i in range(5):
    batch = 20
    X, Y = generate()
    print(model.evaluate(X, Y, batch_size=batch, verbose=0)[1])