title: Classifer partial fit in tensorflow
body: <p>I would like to use SKFLOW to step through the fit of a DNNClassifier, unfortunately code such as:</p>
  
  <pre><code>    step_classifier = skflow.DNNClassifier(hidden_units=[10, 20, 10], n_classes=3)
      for _ in range(50):
        step_classifier = step_classifier.partial_fit(X, Y, steps =1 ,batch_size=32)
        score = metrics.accuracy_score(y, step_classifier.predict(x))
        print("Accuracy: %f" % score)
  </code></pre>
  
  <p>does not produce the desired result -- each iteration of the fit provides the same accuracy: </p>
  
  <pre><code>   Accuracy: 0.315789
       Accuracy: 0.315789
       Accuracy: 0.315789
       Accuracy: 0.315789
     etc
  </code></pre>
  
  <p>It seems in previous versions on this DNNClassifier ie TensorFlowDNNClassifier there was continue_training flag that would produce the desired effect.  This is not available in DNNClassifier.  So how is per epoch stepwise training correctly implemented in SKFLOW?
  Thank you  </p>