title: what is the Tensorflow batch size when you use high-level API tf.contrib.learn.DNNClassifier
body: <pre><code>def binaryClassify_DNN(units,steps,trainingFilePath,testingFilePath,modelPath):
  
      # Data sets
  
      # Load datasets.
      training_set = tf.contrib.learn.datasets.base.load_csv(filename=trainingFilePath,target_dtype=np.float)
      test_set = tf.contrib.learn.datasets.base.load_csv(filename=testingFilePath,target_dtype=np.float)
  
      # Build 3 layer DNN with 10, 20, 10 units respectively.
      classifier = tf.contrib.learn.DNNClassifier(hidden_units=units,n_classes=2,model_dir=modelPath,optimizer=tf.train.ProximalAdagradOptimizer(learning_rate=0.1))
  
      # Fit model.
      classifier.fit(x=training_set.data,
                     y=training_set.target,
                     steps=steps)
  
      # Evaluate accuracy.
      accuracy_score = classifier.evaluate(x=test_set.data,
                                           y=test_set.target)["accuracy"]
      print('Accuracy: {0:f}'.format(accuracy_score))
  </code></pre>
  
  <p>I've coded above source little changed from <a href="https://www.tensorflow.org/versions/r0.10/tutorials/tflearn/index.html#tf-contrib-learn-quickstart" rel="nofollow">https://www.tensorflow.org/versions/r0.10/tutorials/tflearn/index.html#tf-contrib-learn-quickstart</a></p>
  
  <p>As you can see, I didn't add parameter for <code>batch_size</code> which I can add to <code>classifier.fi()</code></p>
  
  <p>I tried executing this code and it seemed that it was looping without batch size.
  I mean that it looks like training with the full size of data instead of mini batch.</p>
  
  <p>Is it true?</p>
  
  <p>I'd like to know what is the default setting for batch size.</p>
  
  <p>Thanks in advance.</p>