title: Does SeparableConv2D include Batch Normalisation and Relu after the Depthwise operation?
body: <p>This question may be similar to <a href="https://stackoverflow.com/questions/54705367/what-is-the-difference-between-separableconv2d-and-conv2d-layers">this</a> and <a href="https://stackoverflow.com/questions/61967172/what-is-depthwiseconv2d-and-separableconv2d-how-is-it-different-from-normal-con">this</a> but in this question I'd like to clear out the difference between DepthwiseConv2D and SeparableConv2D in terms of the activation layers and the batch normalisation layers between the depthwise and pointwise layers.</p>
  <p>The <a href="https://arxiv.org/abs/1704.04861" rel="nofollow noreferrer">mobilenet paper</a> mentions a Depthwise Separable Convolution layer as something like this:
  <a href="https://i.stack.imgur.com/BzCxH.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/BzCxH.png" alt="enter image description here" /></a></p>
  <p>However does the <code>tf.keras</code> version implement the same architecture in the <code>SeparableConv2D</code> layer? If not then what does the layer look like?</p>