code: def single_discriminator(x, filters=128, kernel_size=8,
                           strides=4, pure_mean=False):
    
    with tf.variable_scope("discriminator"):
      net = layers().Conv2D(
          filters, kernel_size, strides=strides, padding="SAME", name="conv1")(x)
      if pure_mean:
        net = tf.reduce_mean(net, [1, 2])
      else:
        net = mean_with_attention(net, "mean_with_attention")
      return net
docs: A simple single-layer convolutional discriminator.