mdn.py 文件源码

def visualize_activations(self, x):
        """
        Visualizes the activations in the mdn caused by a given data minibatch.
        :param x: a minibatch of data
        :return: none
        """

        self.net.visualize_activations(x)

        forwprop = theano.function(
            inputs=[self.input],
            outputs=[self.a, tt.concatenate(self.ms, axis=1) + tt.concatenate([tt.reshape(U, [U.shape[0], -1]) for U in self.Us], axis=1)]
        )
        activations = forwprop(x.astype(dtype))

        for a, title in izip(activations, ['mixing coefficients', 'means', 'scale matrices']):

            fig = plt.figure()
            ax = fig.add_subplot(1, 1, 1)
            ax.imshow(a, cmap='gray', interpolation='none')
            ax.set_title(title)
            ax.set_xlabel('layer units')
            ax.set_ylabel('data points')

        plt.show(block=False)