import tensorflow as tf

                                 activation=tf.nn.relu,
                                 name='l1',
                                 trainable=trainable
                                 )
            mu = 2 * tf.layers.dense(inputs=l1,
                                     units=action_dim,  # number of hidden units
                                     activation=tf.nn.tanh,
                                     name='mu',
                                     trainable=trainable
                                     )
            sigma = tf.layers.dense(inputs=l1,
                                    units=action_dim,  # output units
                                    activation=tf.nn.softplus,  # get action probabilities
                                    name='sigma',
                                    trainable=trainable
                                    )
            norm_dist = tf.distributions.Normal(loc=mu, scale=sigma)
        params = tf.get_collection(tf.GraphKeys.GLOBAL_VARIABLES, scope=name)
        return norm_dist, params

