Two-layer XOR in Keras

keras-xor.py

from __future__ import print_function

import numpy as np
from keras.engine import Input, Model
from keras.layers import Dense

X = np.asarray([[0, 1], [1, 0], [0, 0], [1, 1]])
y = np.asarray([[0], [0], [1], [1]])

input = Input(shape=(2,))
hidden = Dense(5, activation='relu')(input)
output = Dense(1, activation='sigmoid')(hidden)

model = Model(input=input, output=output)
model.compile(optimizer='sgd', loss='mse')

model.fit([X], [y], nb_epoch=10000, verbose=0)
error = model.evaluate([X], [y])
print('Error: {}'.format(error))