MultiRNN and static_rnn error: Dimensions must be equal, but are 256 and 129

Question

I want to build an LSTM network with 3 Layers. Here\'s the code:

num_layers=3
time_steps=10
num_units=128
n_input=1
learning_rate=0.001
n_classes=1
...

x=tf.pla         


        

Answer 1

You should not reuse the same cell for the first and deeper layers, because their inputs are different, hence kernel matrices are different. Try this:

# Extra function is for readability. No problem to inline it.
def make_cell(lstm_size):
  return tf.nn.rnn_cell.BasicLSTMCell(lstm_size, state_is_tuple=True)

network = rnn_cell.MultiRNNCell([make_cell(num_units) for _ in range(num_layers)], 
                                state_is_tuple=True)