code: def nature_cnn(unscaled_images, **conv_kwargs):
      
      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)))
docs: CNN from Nature paper.