def nature_cnn(unscaled_images, **conv_kwargs):
    """
    CNN from Nature paper.
    """
    scaled_images = tf.cast(unscaled_images, tf.float32) / 255.
    activ = tf.nn.relu
    h = activ(
        conv(scaled_images,
             'c1',
             nf=32,
             rf=8,
             stride=4,
             init_scale=np.sqrt(2),
             **conv_kwargs))
    h2 = activ(
        conv(h,
             'c2',
             nf=64,
             rf=4,
             stride=2,
             init_scale=np.sqrt(2),
             **conv_kwargs))
    h3 = activ(
        conv(h2,
             'c3',
             nf=64,
             rf=3,
             stride=1,
             init_scale=np.sqrt(2),
             **conv_kwargs))
    h3 = conv_to_fc(h3)
    return activ(fc(h3, 'fc1', nh=512, init_scale=np.sqrt(2)))
    def network_fn(X):
        h = tf.cast(X, tf.float32) / 255.

        activ = tf.nn.relu
        h = activ(conv(h, 'c1', nf=8, rf=8, stride=4, init_scale=np.sqrt(2), **conv_kwargs))
        h = activ(conv(h, 'c2', nf=16, rf=4, stride=2, init_scale=np.sqrt(2), **conv_kwargs))
        h = conv_to_fc(h)
        h = activ(fc(h, 'fc1', nh=128, init_scale=np.sqrt(2)))
        return h