base_classifier.py 文件源码

def __init__(self, data, target, hidden_layers):
        """ Must submit either a net configuration, or something to load from """
        if hidden_layers == [] and model_filename == "":
            raise Exception("Must provide a net configuration or a file to load from")

        """ Divide the data into training and test """
        self.trainsize = int(len(data) * 5 / 6)
        self.testsize = len(data) - self.trainsize
        self.x_train, self.x_test = np.split(data, [self.trainsize])
        self.y_train, self.y_test = np.split(target, [self.trainsize])

        """ Create the underlying neural network model """
        self.sizes = [len(data[0])]
        self.sizes.extend(hidden_layers)
        self.sizes.append(len(set(target)))
        self.model = L.Classifier(BaseNetwork(self.sizes))

        """ Create the underlying optimizer """
        self.optimizer = optimizers.Adam()
        self.optimizer.setup(self.model)