title: DRQN - Prefix tensor must be either a scalar or vector, but saw tensor
body: <p>In following <a href="https://github.com/awjuliani/DeepRL-Agents/blob/master/Deep-Recurrent-Q-Network.ipynb" rel="nofollow noreferrer">this tutorial</a>, I am receiving the following error: </p>
  
  <p><code>ValueError: prefix tensor must be either a scalar or vector, but saw tensor: Tensor("Placeholder_2:0", dtype=int32)</code></p>
  
  <p>The error originates from these lines:</p>
  
  <pre><code># Take the output from the final convolutional layer and send it to a recurrent layer
  # The input must be reshaped into [batch x trace x units] for rnn processing, and then returned to
  # [batch x units] when sent through the upper levels
  self.batch_size = tf.placeholder(dtype=tf.int32)
  self.convFlat = tf.reshape(slim.flatten(self.conv4), [self.batch_size, self.trainLength, h_size])
  # !!!!This is the line where error city happens!!!!
  self.state_in = rnn_cell.zero_state(self.batch_size, tf.float32)
  </code></pre>
  
  <p>After the network is initialized:</p>
  
  <pre><code>mainQN = Qnetwork(h_size, cell, 'main')
  </code></pre>
  
  <p>This error is still present when solely running the code in a python console so the error is consistent.</p>
  
  <p>I will post more of the code if that will be helpful</p>