예제 #1
0
    def __init__(self, layers, activation_function, activation_args):
        """
            Base class providing the skeleton of a network 
        """
        self.layers = len(layers)
        if (self.layers < 2):
            raise ValueError('Network must contain at least 2 layers, {count} given'.format(count = self.layers))
        self.layer_counts = layers
        for index, layer_size in enumerate(self.layer_counts):
            if (not (layer_size > 0)):
                raise ValueError('Network layers must contain at least 1 node, layer {bad_layer} specifies {bad_count}'.format(
                    bad_layer = index, bad_count = layer_size))
        self.inputs             = int(self.layer_counts[0])
        self.outputs            = int(self.layer_counts[-1])
        self.edge_weights       = GenerateDefaultEdgeWeights(self) 
        self.edge_update_deltas = []
        self.update_edge_weights(self.edge_weights)
        self.bias_weights       = GenerateDefaultBiasWeights(self) 
        self.bias_update_deltas = []
        self.update_bias_weights(self.bias_weights)

        try:
            self.activator = ActivationFunctions.construct(activation_function, **activation_args)
        except Exception as e:
            raise ValueError('Failed to construct activation function, \'{af}\' with args \'{args}\''.format(af = activation_function, args = str(activation_args)))
예제 #2
0
    def test_returns_same_size(self):
        np.random.seed(0)
        elements = 30

        for r in range(1,elements):
            for c in range(1,elements):
                Q = np.random.rand(r,c)
                F = ActivationFunctions.construct('sigmoidal', beta = 1)
                A = F.call(Q)
                self.assertTrue(A.shape == Q.shape)