distribution.py 文件源码

def entropy(self):
        # Differential entropy of Gaussian is:
        #   0.5 * (log(2 * pi * var) + 1)
        #   = 0.5 * (log(2 * pi) + log var + 1)
        with chainer.force_backprop_mode():
            return 0.5 * self.mean.data.shape[1] * (np.log(2 * np.pi) + 1) + \
                0.5 * F.sum(self.ln_var, axis=1)