'image: [0,255]'

def _get_DQN_prediction(self, image):

    image = (image / 255.0)
    with argscope(Conv2D, nl=PReLU.symbolic_function, use_bias=True):
        with argscope(LeakyReLU, alpha=0.01):
            l = LinearWrap(image).Conv2D('conv0', out_channel=32, kernel_shape=8, stride=4).Conv2D('conv1', out_channel=64, kernel_shape=4, stride=2).Conv2D('conv2', out_channel=64, kernel_shape=3).FullyConnected('fc0', 512, nl=LeakyReLU)()
    if (self.method != 'Dueling'):
        Q = FullyConnected('fct', l, self.num_actions, nl=tf.identity)
    else:
        V = FullyConnected('fctV', l, 1, nl=tf.identity)
        As = FullyConnected('fctA', l, self.num_actions, nl=tf.identity)
        Q = tf.add(As, (V - tf.reduce_mean(As, 1, keep_dims=True)))
    return tf.identity(Q, name='Qvalue')
