title: What are the uses of tf.space_to_depth?
body: <p>I am reading this document on <a href="https://www.tensorflow.org/api_docs/python/tf/space_to_depth" rel="nofollow noreferrer"><code>tf.space_to_depth</code></a>. There, it says about the use of the function: </p>
  
  <blockquote>
    <p>This operation is useful for resizing the activations between
    convolutions (but keeping all data), e.g. instead of pooling. It is
    also useful for training purely convolutional models.</p>
  </blockquote>
  
  <p>However, I still don't get a clear understanding of this. Why is it sometimes necessary to resize the activations in a model?</p>