xor.py

import tensorflow as tf


def main():

    training_data = [
        (0, 0, 0),
        (1, 0, 1),
        (0, 1, 1),
        (1, 1, 0)
    ]

    x = [(i[0], i[1]) for i in training_data]
    y = [i[2] for i in training_data]

    model = tf.keras.models.Sequential([
        tf.keras.layers.Dense(12, input_dim=2, activation='relu'),
        tf.keras.layers.Dense(1, activation='sigmoid'),
    ])
    model.compile(tf.keras.optimizers.Adam(learning_rate=0.001),
                  loss='mean_squared_error')

    model.fit(x=x, y=y, epochs=300)

    print(['{} XOR {} = {}'.format(
        x[0], x[1], model.predict([x])[0][0].round()) for x in x])


if __name__ == "__main__":
    main()