Give matrix input

multilabel-matrix-labels.py

#!/usr/bin/env python

"""Neural Network to decide for numbers in 0..15 if they are divisble by
   2, 3, both or none.
"""

import lasagne
from lasagne import layers
from lasagne.updates import nesterov_momentum
from nolearn.lasagne import NeuralNet

import numpy


def nn_example():
    feature_vectors, labels = [], []
    for i in range(2):
        for j in range(2):
            for k in range(2):
                for l in range(2):
                    feature_vectors.append([i, j, k, l])
                    sum_val = 2**0 * i + 2**1 * j + 2**2 * k + 2**3 * l
                    labels.append([sum_val % 2 == 0, sum_val % 3 == 0])
    feature_vectors = numpy.array(feature_vectors, dtype=numpy.float32)
    labels = numpy.array(labels, dtype=numpy.int32)
    print(labels)
    net1 = NeuralNet(layers=[('input', layers.InputLayer),
                             ('hidden', layers.DenseLayer),
                             ('hidden2', layers.DenseLayer),
                             ('output', layers.DenseLayer),
                             ],
                     # layer parameters:
                     input_shape=(None, 4),
                     hidden_num_units=3,
                     hidden2_num_units=2,
                     output_nonlinearity=lasagne.nonlinearities.sigmoid,
                     output_num_units=2,

                     # optimization method:
                     update=nesterov_momentum,
                     update_learning_rate=0.01,
                     update_momentum=0.9,

                     max_epochs=1000,
                     verbose=1,
                     )

    # Train the network
    net1.fit(feature_vectors, labels)

    # Try the network
    print("Predicted: %s" % str(net1.predict_proba([[0, 0, 1, 0]])))

if __name__ == '__main__':
    nn_example()