mlp.py 文件源码

def __init__(self, input_size, output_size, hidden_sizes, activation = T.nnet.sigmoid):

        self.hidden_layers = []
        self.params = []
        self.input = T.matrix('x')
        self.target = T.matrix('y')

        for i, layer_size in enumerate(hidden_sizes):
            if i == 0:
               layer_input_size = input_size
               layer_input = self.input
            else:
                layer_input_size = hidden_sizes[i - 1]
                layer_input = self.hidden_layers[-1].output
            layer = Layer(layer_input, layer_input_size, layer_size, activation = activation)
            self.hidden_layers.append(layer)
            self.params.extend(layer.params)

        self.output_layer = Layer(self.hidden_layers[-1].output, hidden_sizes[-1], output_size)
        self.params.extend(self.output_layer.params)
        self.output = self.output_layer.output
        self.cost = T.sum((self.output - self.target)**2)