ProjE_softmax.py 文件源码

def __l1_normalize(x, dim, epsilon=1e-12, name=None):
        square_sum = tf.reduce_sum(tf.abs(x), [dim], keep_dims=True)
        x_inv_norm = tf.rsqrt(tf.maximum(square_sum, epsilon))
        return tf.mul(x, x_inv_norm, name=name)