title: Tensorflow re-use rnn_seq2seq model
body: <p>I'm trying to create a program with tensorflow to do something with a sequence. An option in the tf.nn.seq2seq functions is the feed_previous parameter. This is something that I CAN use at train-time, but not at evaluation/runtime. Currently I tried this:</p>
  
  <pre><code>(outputs_dict,state_dict) = tf.nn.seq2seq.one2many_rnn_seq2seq(enc_inp,decoder_inputs_dictionary,cell, vocab_size, decoder_symbols_dictionary,embedding_size=embedding_dim)
  (evaluation_dict,evaluation_state_dict) = tf.nn.seq2seq.one2many_rnn_seq2seq(enc_inp,decoder_inputs_dictionary,cell, vocab_size, decoder_symbols_dictionary,embedding_size=embedding_dim,feed_previous=True)
  </code></pre>
  
  <p>But I get the error: "ValueError: Variable one2many_rnn_seq2seq/RNN/EmbeddingWrapper/embedding already exists, disallowed. Did you mean to set reuse=True in VarScope?" </p>
  
  <p>Does anybody know how to</p>
  
  <ul>
  <li>reuse my model so I can use feed_previous during training, but not during evaluation?</li>
  </ul>