def predict(self, input_array):
inputs = Matrix.from_array(input_array)
hidden = Matrix.multiply_matrix(self.weights_ih, inputs)
hidden = Matrix.add_matrix(hidden, self.bias_h)
hidden.map(NeuralNetwork.sigmoid)
output = Matrix.multiply_matrix(self.weights_ho, hidden)
output = Matrix.add_matrix(output, self.bias_o)
output.map(NeuralNetwork.sigmoid)
return Matrix.to_array(output)
def train(self, input_array, targets_array):
inputs = Matrix.from_array(input_array)
hidden = Matrix.multiply_matrix(self.weights_ih, inputs)
hidden = Matrix.add_matrix(hidden, self.bias_h)
hidden.map(NeuralNetwork.sigmoid)
outputs = Matrix.multiply_matrix(self.weights_ho, hidden)
outputs = Matrix.add_matrix(outputs, self.bias_o)
outputs.map(NeuralNetwork.sigmoid)
targets = Matrix.from_array(targets_array)
outputs_errors = Matrix.subtract_matrix(targets, outputs)
gradients = Matrix.map_matrix(outputs, self.dsigmoid)
gradients = Matrix.multiply_matrix(gradients, outputs_errors)
gradients.multiply(self.lr)
self.bias_o = Matrix.add_matrix(self.bias_o, gradients)
hidden_t = Matrix.transpose_matrix(hidden)
weight_ho_deltas = Matrix.multiply_matrix(gradients, hidden_t)
self.weights_ho = Matrix.add_matrix(self.weights_ho, weight_ho_deltas)
weights_t = Matrix.transpose_matrix(self.weights_ho)
hidden_errors = Matrix.multiply_matrix(weights_t, outputs_errors)
hidden_gradient = Matrix.map_matrix(hidden, self.dsigmoid)
hidden_gradient = Matrix.multiply_matrix(hidden_gradient,
hidden_errors)
hidden_gradient.multiply(self.lr)
self.bias_h = Matrix.add_matrix(self.bias_h, hidden_gradient)
inputs_t = Matrix.transpose_matrix(inputs)
weight_ih_deltas = Matrix.multiply_matrix(hidden_gradient, inputs_t)
self.weights_ih = Matrix.add_matrix(self.weights_ih, weight_ih_deltas)
def test_add_matrix(self):
first_matrix = Matrix([[1, 2], [3, 4]])
second_matrix = Matrix([[5, 6], [7, 8]])
self.assertEqual(first_matrix.add_matrix(second_matrix),
[[6, 8], [10, 12]])
def test_add_matrix(self):
a = Matrix([[1, 2], [3, 4]])
b = Matrix([[5, 6], [7, 8]])
self.assertEqual(a.add_matrix(b), [[6, 8], [10, 12]])
