a3_entity_network.py 文件源码

def activation(self,features, scope=None):  # scope=None
        with tf.variable_scope(scope, 'PReLU', initializer=self.initializer):
            alpha = tf.get_variable('alpha', features.get_shape().as_list()[1:])
            pos = tf.nn.relu(features)
            neg = alpha * (features - tf.abs(features)) * 0.5
            return pos + neg