title: cannot add op with name
body: <p>I have a problem with freeze_graph function:</p>
  
  <blockquote>
    <p>ValueError: cannot add op with name Conv1/W1/Adam as that name is already used</p>
  </blockquote>
  
  <p>In this line:</p>
  
  <pre><code>def export_model(input_node_names, output_node_name):
      my_freeze_graph.freeze_graph('out/' + MODEL_NAME + '.pbtxt', None, False, 'out/' + MODEL_NAME + '.chkp', output_node_name, "save/restore_all", "save/Const:0", 'out/frozen_' + MODEL_NAME + '.pb', True, "")
  </code></pre>
  
  <p>My model structure:</p>
  
  <pre><code>def get_model(input, dropout):
      with tf.name_scope('Conv1'):
          input_4D = tf.reshape(input, [-1, HEIGHT, WIDTH, 1])
          w1 = tf.Variable(tf.truncated_normal([12, 8, 1, 44], stddev=0.01), name='W1')
          b1 = tf.Variable(tf.zeros([44]), name='B1')
          conv1 = tf.nn.conv2d(input_4D, w1, strides=[1, 1, 1, 1], padding='SAME')
          act1 = tf.nn.relu(conv1 + b1)
          drop1 = tf.nn.dropout(act1, dropout)
          max_pool1 = tf.nn.max_pool(drop1, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1], padding='SAME')
          tf.summary.histogram('weights', w1)
          tf.summary.histogram('biases', b1)
          tf.summary.histogram('activations', act1)
          tf.summary.histogram('dropouts', drop1)
  
      with tf.name_scope('Conv2'):
          w2 = tf.Variable(tf.truncated_normal([6, 4, 44, 44], stddev=0.01), name='W2')
          b2 = tf.Variable(tf.zeros([44]), name='B2')
          conv2 = tf.nn.conv2d(max_pool1, w2, strides=[1, 1, 1, 1], padding='SAME')
          act2 = tf.nn.relu(conv2 + b2)
          drop2 = tf.nn.dropout(act2, dropout)
          tf.summary.histogram('weights', w2)
          tf.summary.histogram('biases', b2)
          tf.summary.histogram('activations', act2)
          tf.summary.histogram('dropouts', drop2)
          conv_shape = drop2.get_shape()
          count = int(conv_shape[1] * conv_shape[2] * conv_shape[3])
          flat_output = tf.reshape(drop2, [-1, count])
  
      with tf.name_scope('FC'):
          w3 = tf.Variable(tf.truncated_normal([count, NUM_LABELS], stddev=0.01), name='W3')
          b3 = tf.Variable(tf.zeros([NUM_LABELS]), name='B3')
          fc = tf.add(tf.matmul(flat_output, w3), b3)
          tf.summary.histogram('weights', w3)
          tf.summary.histogram('biases', b3)
  
      return fc
  </code></pre>
  
  <p>What did I do wrong?</p>
  
  <p>P.S. Tensorflow version is 1.2.1, python version is 3.6.4</p>