A very simple Keras XOR Modell and training and testing

Simple Keras XOR

from keras.models import Sequential
from keras.layers import Dense
from keras.optimizers import SGD

X = [[0.0, 0.0],
     [0.0, 1.0],
     [1.0, 0.0],
     [0.0, 0.0]]

Y = [[0.0],
     [1.0],
     [1.0],
     [0.0]]


sgd = SGD(lr=0.1)


def create_network():
    model = Sequential()
    model.add(Dense(8, input_dim=2, activation='tanh'))
    model.add(Dense(1, activation='sigmoid'))
    model.compile(loss='binary_crossentropy', optimizer=sgd)

    return model


def train(model):
    model.fit(X, Y, epochs=1000, batch_size=4)
    return model


def predict(model):
    return model.predict(X)


if __name__ == "__main__":
    model = create_network()
    before_training = predict(model)
    train(model)
    print("Before Training")
    print(before_training)
    print("After Training")
    print(predict(model))