def test_layer(self):
n_inputs = 10
n_hidden = 20
x = tf.ones([1, n_inputs])
input_layer = Layer(n_units=n_inputs, activation=x)
nn = NeuralNetwork(input_layer)
self.assertEqual(nn.size(), 1)
# add a layer with biases
hidden_layer = Layer(n_hidden, activation=tf.identity)
nn.add_layer(hidden_layer, biased=True)
layer_0 = nn.layer(0)
layer_1 = nn.layer(1)
self.assertEqual(layer_0, input_layer)
self.assertEqual(layer_1, hidden_layer)
