title: Is there a simple way to set epochs when using TFRecords with Tensorflow Estimators
body: <p>There is a nice way to set epochs when feeding numpy arrays into an estimator </p>
  
  <pre><code>  tf.estimator.inputs.numpy_input_fn(
       x,
       y=None,
       batch_size=128,
       num_epochs=1 ,
       shuffle=None,
       queue_capacity=1000,
       num_threads=1  
     )
  </code></pre>
  
  <p>But I can't track down a similar method with TFRecords, most people seem to just stick it in a loop  </p>
  
  <pre><code> i = 0 
   while ( i &lt; 100000):
     model.train(input_fn=input_fn, steps=100)
  </code></pre>
  
  <p>Is there a clean way to explicitly set the number of epochs for TFRecords with estimators ?</p>