Method summary

neural_network/back_propagation_neural_network.py:120–124

(self)

                layer.initializer(self.layers[i - 1].units)

    def summary(self):
        for i, layer in enumerate(self.layers[:]):
            print(f"------- layer {i} -------")
            print("weight.shape ", np.shape(layer.weight))
            print("bias.shape ", np.shape(layer.bias))

    def train(self, xdata, ydata, train_round, accuracy):
        self.train_round = train_round