division.py

#!/usr/bin/env python

from keras.layers.core import Dense
from keras.models import Sequential
from keras.optimizers import RMSprop, Adadelta, Adagrad, Adam, SGD
from keras.callbacks import Callback

import numpy as np

class Test(Callback):
    test = np.matrix('1 2; 2 4; 4 2; 2 1; 1 1')
    def on_epoch_end(self, epoch, logs={}):
        print self.test
        print self.model.predict(self.test, self.test.shape[0])

if __name__ == '__main__':
    np.random.seed(1)
    X = np.random.randint(-100, 100, size=(100000, 2))# + np.random.normal()
    y = X[:, 0] / X[:, 1]

    model = Sequential()
    model.add(Dense(128, activation='sigmoid', input_dim=X.shape[1]))
    model.add(Dense(64, activation='linear'))
    model.add(Dense(32, activation='sigmoid'))
    #model.add(Dense(32, activation='tanh'))
    #model.add(Dense(16, activation='tanh'))
    #model.add(Dense(1000, activation='tanh'))
    #model.add(Dense(1000, activation='tanh'))
    model.add(Dense(1))

    opt = Adadelta()
    TestCallback = Test()

    model.compile(optimizer=opt, loss='mse')

    history = model.fit(X, y, batch_size=100, nb_epoch=100, verbose=1, validation_split=0.2, shuffle=True, callbacks=[TestCallback])