loopprocessing.py 文件源码

def __call__(X):
        """ Predict the output from prev and scale the result on [-1, 1]
        Use sigmoid activation
        Args:
            X (tf.Tensor): the input
        Return:
            tf.Ops: the activate_and_scale operator
        """
        # TODO: Use tanh instead ? tanh=2*sigm(2*x)-1
        with tf.name_scope('activate_and_scale'):
            return tf.sub(tf.mul(2.0, tf.nn.sigmoid(X)), 1.0)  # x_{i} = 2*sigmoid(y_{i-1}) - 1