diff options
Diffstat (limited to 'tensorflow/contrib/rnn/python/ops/rnn_cell.py')
| -rw-r--r-- | tensorflow/contrib/rnn/python/ops/rnn_cell.py | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/tensorflow/contrib/rnn/python/ops/rnn_cell.py b/tensorflow/contrib/rnn/python/ops/rnn_cell.py index 9c5e9fec9d..ecce1d22f0 100644 --- a/tensorflow/contrib/rnn/python/ops/rnn_cell.py +++ b/tensorflow/contrib/rnn/python/ops/rnn_cell.py @@ -79,7 +79,7 @@ class CoupledInputForgetGateLSTMCell(rnn_cell_impl.RNNCell): The default non-peephole implementation is based on: - http://deeplearning.cs.cmu.edu/pdfs/Hochreiter97_lstm.pdf + http://www.bioinf.jku.at/publications/older/2604.pdf S. Hochreiter and J. Schmidhuber. "Long Short-Term Memory". Neural Computation, 9(8):1735-1780, 1997. @@ -1110,14 +1110,14 @@ class AttentionCellWrapper(rnn_cell_impl.RNNCell): if input_size is None: input_size = inputs.get_shape().as_list()[1] inputs = _linear([inputs, attns], input_size, True) - lstm_output, new_state = self._cell(inputs, state) + cell_output, new_state = self._cell(inputs, state) if self._state_is_tuple: new_state_cat = array_ops.concat(nest.flatten(new_state), 1) else: new_state_cat = new_state new_attns, new_attn_states = self._attention(new_state_cat, attn_states) with vs.variable_scope("attn_output_projection"): - output = _linear([lstm_output, new_attns], self._attn_size, True) + output = _linear([cell_output, new_attns], self._attn_size, True) new_attn_states = array_ops.concat( [new_attn_states, array_ops.expand_dims(output, 1)], 1) new_attn_states = array_ops.reshape( |