Creates a bidirectional recurrent neural network. Similar to the unidirectional case above (rnn) but takes input and builds independent forward and backward RNNs with the final forward and backward outputs depth-concatenated, such that the output will have the format [time][batch][cell_fw.o
(cell_fw,
cell_bw,
inputs,
initial_state_fw=None,
initial_state_bw=None,
dtype=None,
sequence_length=None,
scope=None)
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