from __future__ import print_function
    import keras
    from keras.models import Sequential
    from keras.layers import Dense
    from keras.utils import to_categorical
    import numpy as np

    np.random.seed(0)

    X = np.array([[0.1, 0.5], [1.1, 2.3], [-1.1, -2.3], [-1.5, -2.5]])
    y = np.array([0, 1, 2, 2])

    y_enc = to_categorical(y)

    W = np.array([[0.1, 0.2, 0.3],
                  [0.1, 0.2, 0.3]])

    b = np.array([0.01, 0.1, 0.1])

    model = Sequential()
    model.add(Dense(3, weights=[W,b] , input_dim=2))
    model.summary()
    model.compile(loss='categorical_crossentropy', optimizer='Adam')
    print(model.evaluate(X , y_enc))