def bidirectional_rnn(cell_fw, cell_bw, inputs,
initial_state_fw=None, initial_state_bw=None,
dtype=None, sequence_length=None, scope=None):
flat_inputs = flatten(inputs, 2) # [-1, J, d]
flat_len = None if sequence_length is None else tf.cast(flatten(sequence_length, 0), 'int64')
(flat_fw_outputs, flat_bw_outputs), final_state = \
_bidirectional_rnn(cell_fw, cell_bw, flat_inputs, sequence_length=flat_len,
initial_state_fw=initial_state_fw, initial_state_bw=initial_state_bw,
dtype=dtype, scope=scope)
fw_outputs = reconstruct(flat_fw_outputs, inputs, 2)
bw_outputs = reconstruct(flat_bw_outputs, inputs, 2)
# FIXME : final state is not reshaped!
return (fw_outputs, bw_outputs), final_state
def bidirectional_rnn(cell_fw, cell_bw, inputs,
initial_state_fw=None, initial_state_bw=None,
dtype=None, sequence_length=None, scope=None):
flat_inputs = flatten(inputs, 2) # [-1, J, d]
flat_len = None if sequence_length is None else tf.cast(flatten(sequence_length, 0), 'int64')
(flat_fw_outputs, flat_bw_outputs), final_state = \
_bidirectional_rnn(cell_fw, cell_bw, flat_inputs, sequence_length=flat_len,
initial_state_fw=initial_state_fw, initial_state_bw=initial_state_bw,
dtype=dtype, scope=scope)
fw_outputs = reconstruct(flat_fw_outputs, inputs, 2)
bw_outputs = reconstruct(flat_bw_outputs, inputs, 2)
# FIXME : final state is not reshaped!
return (fw_outputs, bw_outputs), final_state