title: How can tensorflow feature columns be used for repeatable features?
body: <p>I would like to train a sparse logistic regression to classify users in two classes. One of my features is the users' interests which is non-exclusive (e.g. a user can be interested in cars, books and food) and variable in number: a user may have 5 interests, while another may have only 3, in contrast to the examples shown in the <a href="https://www.tensorflow.org/versions/r0.9/tutorials/wide/index.html" rel="nofollow">Deep and Wide tutorial</a> (age, education, etc.). I would like to reuse the code from the deep and wide tutorial as much as possible because eventually I would like to extend my model to have a deep component too. What the easiest way to achieve that? I'm also interested in maintaining the time complexity for training/scoring an example to <code>O(active_features)</code>.</p>