Rank error in tf.nn.dynamic_rnn

Question

I am trying to build a CNN + RNN model and I am getting the following error. Any help will be appreciated.

fc2 has shape (?,4096)

cell = tf.contrib.rnn.BasicLSTMCell(self.rnn_hidden_units)
stack = tf.contrib.rnn.MultiRNNCell([cell]*self.rnn_layers)
initial_state = cell.zero_state(self.batch_size, tf.float32)
initial_state = tf.identity(initial_state, name='initial_state')
outputs, _ = tf.nn.dynamic_rnn(stack, fc2,dtype=tf.float32)

File "rcnn.py", line 182, in model outputs, _ = tf.nn.dynamic_rnn(stack, [fc2],dtype=tf.float32)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/rnn.py", line 574, in dynamic_rnn dtype=dtype)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/rnn.py", line 637, in _dynamic_rnn_loop for input_ in flat_input)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/ops/rnn.py", line 637, in for input_ in flat_input)
File "/usr/local/lib/python2.7/dist-packages/tensorflow/python/framework/tensor_shape.py", line 649, in with_rank_at_least raise ValueError("Shape %s must have rank at least %d" % (self, rank)) ValueError: Shape (4096, ?) must have rank at least 3

Answer 1

Copying the answer of @jdehesa from his comment for better visibility:

The error seems fairly clear, tf.nn.dynamic_rnn expects a 3-dimensional tensor as input (i.e. rank 3), but fc2 has only two dimensions. The shape of fc2 should be something like (<batch_size>, <max_time>, <num_features>) (or (<max_time>, <batch_size>, <num_features>) if you pass time_major=True)

Answer 2

The default input of tf.nn.dynamic_rnn has a dimension of 3 (Batchsize, sequence_length, num_features). Since your num_features is 1 you can expand your fc_seq with

fc2 = tf.expand_dims(fc2, axis = 2)

and then use the code you have above.