title: Can tensorflow handle categorical features with multiple inputs within one column?
body: <p>For example, I have data in the following csv format:</p>
  
  <blockquote>
    <p>1, 2, 1:3:4, 2</p>
    
    <p>0, 1, 3:5, 1</p>
    
    <p>...</p>
  </blockquote>
  
  <p>Each column seperated by comma represent one feature. Normally, a feature is one-hot(<em>e.g. col0, col1, col3</em>), but in this case, the feature for <em>col2</em> has multiple inputs(seperated by colon). </p>
  
  <p>I'm sure tensorflow can handle one-hot feature with <strong>sparse tensor</strong>, but I'm not sure if it could handle feature with multiple inputs like <em>col2</em>?</p>
  
  <p>And if ok, how should it be represented in tensorflow's <strong>sparse tensor</strong>?</p>