title: Variable bidirectional_rnn/fw/lstm_cell/weights already exists, disallowed. Did you mean to set reuse=True in VarScope? Originally defined at:
body: <p>When I call the function tf.nn.bidirectional_dynamic_rnn, it returns 
  Variable bidirectional_rnn/fw/lstm_cell/weights already exists, disallowed. Did you mean to set reuse=True in VarScope? Originally defined at:</p>
  
  <p>My code:</p>
  
  <pre><code>tf.reset_default_graph()
  sess = tf.InteractiveSession()
  PAD = 0
  EOS = 1
  
  sequence_size = 10 #vocal_size
  input_embedding_size = 20 #length of sequence
  
  encoder_hidden_units = 20
  decoder_hidden_units = encoder_hidden_units * 2
  
  encoder_inputs = tf.placeholder(shape=(None, None), dtype=tf.int32, 
  name='encoder_inputs')
  #length of each sequence in the batch
  encoder_inputs_length = tf.placeholder(shape=(None,), dtype=tf.int32, 
  name='encoder_inputs_length')
  decoder_targets = tf.placeholder(shape=(None, None), dtype=tf.int32, 
  name='decoder_targets')
  embeddings = tf.Variable(tf.random_uniform([sequence_size, 
  input_embedding_size], -1.0, 1), dtype=tf.float32 )
  encoder_inputs_embedded = tf.nn.embedding_lookup(embeddings, 
  encoder_inputs)
  
  encoder_cell = tf.contrib.rnn.LSTMCell(encoder_hidden_units)
  ( (encoder_fw_outputs,
  encoder_bw_outputs),
  (encoder_fw_final_state,
  encoder_bw_final_state)) = (
  tf.nn.bidirectional_dynamic_rnn(cell_fw=encoder_cell,
                                  cell_bw=encoder_cell,
                                  inputs=encoder_inputs_embedded,
                                  sequence_length=encoder_inputs_length,
                                  dtype=tf.float32, time_major=False)
  )
  </code></pre>
  
  <p>I got this as error:</p>
  
  <pre><code>ValueError                   Traceback (most recent call last)
  &lt;ipython-input-211-41a8d71d81df&gt; in &lt;module&gt;()
   23                                     
  inputs=encoder_inputs_embedded,
   24                                     
   sequence_length=encoder_inputs_length,
    ---&gt; 25                                     dtype=tf.float32, 
   time_major=False)
   26     )
   27 
  
  /home/cesar/anaconda2/envs/tensorflow/lib/python2.7/site-
  packages/tensorflow/python/ops/rnn.pyc in 
  bidirectional_dynamic_rnn(cell_fw, cell_bw, inputs, sequence_length, 
  initial_state_fw, initial_state_bw, dtype, parallel_iterations, 
  swap_memory, time_major, scope)
  348           initial_state=initial_state_fw, dtype=dtype,
  349           parallel_iterations=parallel_iterations, 
  swap_memory=swap_memory,
  --&gt; 350           time_major=time_major, scope=fw_scope)
  351 
  352     # Backward direction
  
  /home/cesar/anaconda2/envs/tensorflow/lib/python2.7/site-
  packages/tensorflow/python/ops/rnn.pyc in dynamic_rnn(cell, inputs, 
  sequence_length, initial_state, dtype, parallel_iterations, 
  swap_memory, time_major, scope)
  544         swap_memory=swap_memory,
  545         sequence_length=sequence_length,
  --&gt; 546         dtype=dtype)
  547 
  548     # Outputs of _dynamic_rnn_loop are always shaped [time, batch, 
  depth].
  
  /home/cesar/anaconda2/envs/tensorflow/lib/python2.7/site-
  packages/tensorflow/python/ops/rnn.pyc in _dynamic_rnn_loop(cell, 
  inputs, initial_state, parallel_iterations, swap_memory, 
  sequence_length, dtype)
  711       loop_vars=(time, output_ta, state),
  712       parallel_iterations=parallel_iterations,
   --&gt; 713       swap_memory=swap_memory)
  714 
  715   # Unpack final output if not using output tuples.
  
   /home/cesar/anaconda2/envs/tensorflow/lib/python2.7/site-
   packages/tensorflow/python/ops/control_flow_ops.pyc in 
   while_loop(cond, body, loop_vars, shape_invariants, 
   parallel_iterations, back_prop, swap_memory, name)
   2603     context = WhileContext(parallel_iterations, back_prop, 
   swap_memory, name)
   2604     ops.add_to_collection(ops.GraphKeys.WHILE_CONTEXT, context)
   -&gt; 2605     result = context.BuildLoop(cond, body, loop_vars, 
   shape_invariants)
   2606     return result
    2607 
  
   /home/cesar/anaconda2/envs/tensorflow/lib/python2.7/site-
   packages/tensorflow/python/ops/control_flow_ops.pyc in 
   BuildLoop(self, pred, body, loop_vars, shape_invariants)
   2436       self.Enter()
   2437       original_body_result, exit_vars = self._BuildLoop(
   -&gt; 2438           pred, body, original_loop_vars, loop_vars, 
  shape_invariants)
   2439     finally:
   2440       self.Exit()
  
   /home/cesar/anaconda2/envs/tensorflow/lib/python2.7/site-
   packages/tensorflow/python/ops/control_flow_ops.pyc in 
  _BuildLoop(self, pred, body, original_loop_vars, loop_vars, 
   shape_invariants)
   2386         structure=original_loop_vars,
   2387         flat_sequence=vars_for_body_with_tensor_arrays)
    -&gt; 2388     body_result = body(*packed_vars_for_body)
   2389     if not nest.is_sequence(body_result):
   2390       body_result = [body_result]
  
  /home/cesar/anaconda2/envs/tensorflow/lib/python2.7/site-
  packages/tensorflow/python/ops/rnn.pyc in _time_step(time, 
  output_ta_t, state)
  694           call_cell=call_cell,
  695           state_size=state_size,
  --&gt; 696           skip_conditionals=True)
  697     else:
  698       (output, new_state) = call_cell()
  
  /home/cesar/anaconda2/envs/tensorflow/lib/python2.7/site-
  packages/tensorflow/python/ops/rnn.pyc in _rnn_step(time, 
  sequence_length, min_sequence_length, max_sequence_length, 
  zero_output, state, call_cell, state_size, skip_conditionals)
  175     # steps.  This is faster when max_seq_len is equal to the 
  number of unrolls
  176     # (which is typical for dynamic_rnn).
  --&gt; 177     new_output, new_state = call_cell()
  178     nest.assert_same_structure(state, new_state)
  179     new_state = nest.flatten(new_state)
  
  /home/cesar/anaconda2/envs/tensorflow/lib/python2.7/site-
  packages/tensorflow/python/ops/rnn.pyc in &lt;lambda&gt;()
  682 
  683     input_t = nest.pack_sequence_as(structure=inputs, 
  flat_sequence=input_t)
   --&gt; 684     call_cell = lambda: cell(input_t, state)
  685 
  686     if sequence_length is not None:
  
  /home/cesar/anaconda2/envs/tensorflow/lib/python2.7/site-
  packages/tensorflow/contrib/rnn/python/ops/core_rnn_cell_impl.pyc in 
  __call__(self, inputs, state, scope)
  336       # i = input_gate, j = new_input, f = forget_gate, o = 
  output_gate
  337       lstm_matrix = _linear([inputs, m_prev], 4 * self._num_units, 
  bias=True,
   --&gt; 338                             scope=scope)
  339       i, j, f, o = array_ops.split(
  340           value=lstm_matrix, num_or_size_splits=4, axis=1)
  
  /home/cesar/anaconda2/envs/tensorflow/lib/python2.7/site-
  packages/tensorflow/contrib/rnn/python/ops/core_rnn_cell_impl.pyc in 
  _linear(args, output_size, bias, bias_start, scope)
  745   with vs.variable_scope(scope) as outer_scope:
  746     weights = vs.get_variable(
   --&gt; 747         "weights", [total_arg_size, output_size], 
   dtype=dtype)
  748     if len(args) == 1:
  749       res = math_ops.matmul(args[0], weights)
  
  /home/cesar/anaconda2/envs/tensorflow/lib/python2.7/site-
  packages/tensorflow/python/ops/variable_scope.pyc in 
  get_variable(name, shape, dtype, initializer, regularizer, trainable, 
  collections, caching_device, partitioner, validate_shape, 
  custom_getter)
  986       collections=collections, caching_device=caching_device,
  987       partitioner=partitioner, validate_shape=validate_shape,
   --&gt; 988       custom_getter=custom_getter)
  989 get_variable_or_local_docstring = (
  990     """%s
  
  /home/cesar/anaconda2/envs/tensorflow/lib/python2.7/site-
  packages/tensorflow/python/ops/variable_scope.pyc in 
  get_variable(self, var_store, name, shape, dtype, initializer, 
  regularizer, trainable, collections, caching_device, partitioner, 
  validate_shape, custom_getter)
  888           collections=collections, caching_device=caching_device,
  889           partitioner=partitioner, validate_shape=validate_shape,
  --&gt; 890           custom_getter=custom_getter)
  891 
  892   def _get_partitioned_variable(self,
  
  /home/cesar/anaconda2/envs/tensorflow/lib/python2.7/site-
  packages/tensorflow/python/ops/variable_scope.pyc in 
  get_variable(self, name, shape, dtype, initializer, regularizer, 
  reuse, trainable, collections, caching_device, partitioner, 
  validate_shape, custom_getter)
  346           reuse=reuse, trainable=trainable, 
  collections=collections,
  347           caching_device=caching_device, partitioner=partitioner,
  --&gt; 348           validate_shape=validate_shape)
  349 
  350   def _get_partitioned_variable(
  
  /home/cesar/anaconda2/envs/tensorflow/lib/python2.7/site-
  packages/tensorflow/python/ops/variable_scope.pyc in 
  _true_getter(name, shape, dtype, initializer, regularizer, reuse, 
  trainable, collections, caching_device, partitioner, validate_shape)
  331           initializer=initializer, regularizer=regularizer, 
  reuse=reuse,
  332           trainable=trainable, collections=collections,
  --&gt; 333           caching_device=caching_device, 
  validate_shape=validate_shape)
  334 
  335     if custom_getter is not None:
  
  /home/cesar/anaconda2/envs/tensorflow/lib/python2.7/site-
  packages/tensorflow/python/ops/variable_scope.pyc in 
  _get_single_variable(self, name, shape, dtype, initializer, 
  regularizer, partition_info, reuse, trainable, collections, 
  caching_device, validate_shape)
  637                          " Did you mean to set reuse=True in 
  VarScope? "
  638                          "Originally defined at:\n\n%s" % (
  --&gt; 639                              name, 
  "".join(traceback.format_list(tb))))
  640       found_var = self._vars[name]
  641       if not shape.is_compatible_with(found_var.get_shape()):
  
  ValueError: Variable bidirectional_rnn/fw/lstm_cell/weights already 
  exists, disallowed. Did you mean to set reuse=True in VarScope? 
  Originally defined at:
  
  File "/home/cesar/anaconda2/envs/tensorflow/lib/python2.7/site-
  packages/tensorflow/contrib/rnn/python/ops/core_rnn_cell_impl.py", 
  line 
  747, in _linear
  "weights", [total_arg_size, output_size], dtype=dtype)
   File "/home/cesar/anaconda2/envs/tensorflow/lib/python2.7/site-
   packages/tensorflow/contrib/rnn/python/ops/core_rnn_cell_impl.py",      
   line 338, in __call__
   scope=scope)
   File "&lt;ipython-input-23-f4f28501e56f&gt;", line 24, in &lt;module&gt;
   time_major=True
  </code></pre>