title: Feed multiple Inputs into Graph using data.dataset API
body: <p>I am trying to feed data to CTC LSTM network using tensorflow am using the Dataset API to feed data to placeholders. For that I have created a </p>
  
  <p>iterator.get_next() iter_val whose output is </p>
  
  <pre><code>(&lt;tf.Tensor 'IteratorGetNext_1:0' shape=(?, ?, 16) dtype=float32&gt;,
   &lt;tf.Tensor 'IteratorGetNext_1:1' shape=(?, ?) dtype=int32&gt;,
   &lt;tf.Tensor 'IteratorGetNext_1:2' shape=(?, 1) dtype=int32&gt;,
   &lt;tf.Tensor 'IteratorGetNext_1:3' shape=(?, 1) dtype=int32&gt;)
  </code></pre>
  
  <p>My placeholders are </p>
  
  <pre><code>train_inputs = tf.placeholder(tf.float32, [None, None, num_features])
  target_inputs = tf.placeholder(tf.int32, [None, None])
  seq_len = tf.placeholder(tf.int32, [None,1])
  out_len = tf.placeholder(tf.int32, [None,1])
  
  loss = Result of operations of the above placeholders
  optimizer = tf.train.GradientDescentOptimizer(0.01)
  train = optimizer.minimize(loss)
  </code></pre>
  
  <p>when I try to run the session as</p>
  
  <pre><code>with tf.Session() as sess:
      for i in range(num_epochs):
        sess.run(iter_val)
        _, loss_value = sess.run((train, loss))
        print(loss_value)
  </code></pre>
  
  <p>I get the error</p>
  
  <blockquote>
    <p>InvalidArgumentError: You must feed a value for placeholder tensor
    'Placeholder_11' with dtype int32 and shape [?,1]      [[node
    Placeholder_11 (defined at :30) ]]</p>
  </blockquote>
  
  <p>I am clearly not feeding this session properly so how do I feed the session properly</p>