[incubator-mxnet] branch master updated: Update model_parallel_lstm.md (#9447)

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The following commit(s) were added to refs/heads/master by this push:
     new a182aec  Update model_parallel_lstm.md (#9447)
a182aec is described below

commit a182aecee5185a276fac6a0ec3c6825f93c94a22
Author: Haibin Lin <li...@gmail.com>
AuthorDate: Tue Jan 16 11:53:30 2018 -0800

    Update model_parallel_lstm.md (#9447)
---
 docs/faq/model_parallel_lstm.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/docs/faq/model_parallel_lstm.md b/docs/faq/model_parallel_lstm.md
index 4a02288..1e367eb 100644
--- a/docs/faq/model_parallel_lstm.md
+++ b/docs/faq/model_parallel_lstm.md
@@ -65,15 +65,15 @@ Although the LSTM layers consume less memory than the decoder/encoder layers, th
 Thus, the partition on the left will be faster than the one on the right
 because the workload is more evenly distributed.
 
-Currently, the layer partition is implemented in [lstm.py](https://github.com/eric-haibin-lin/mxnet/blob/master/example/model-parallel-lstm/lstm.py#L187) and configured in [lstm_ptb.py](https://github.com/eric-haibin-lin/mxnet/blob/master/example/model-parallel-lstm/lstm.py#L187) using the `group2ctx` option.
+Currently, the layer partition is implemented in [lstm.py](https://github.com/apache/incubator-mxnet/blob/master/example/model-parallel/lstm/lstm.py#L171) and configured in [lstm_ptb.py](https://github.com/apache/incubator-mxnet/blob/master/example/model-parallel/lstm/lstm_ptb.py#L97-L102) using the `group2ctx` option.
 
 ## Apply Bucketing to Model Parallelism
 
 To achieve model parallelism while using bucketing,
 you need to unroll an LSTM model for each bucket
 to obtain an executor for each.
-For details about how the model is bound, see [lstm.py](https://github.com/eric-haibin-lin/mxnet/blob/master/example/model-parallel-lstm/lstm.py#L154).
+For details about how the model is bound, see [lstm.py](https://github.com/apache/incubator-mxnet/blob/master/example/model-parallel/lstm/lstm.py#L225-L235).
 
 On the other hand, because model parallelism partitions the model/layers,
 the input data has to be transformed/transposed to the agreed shape.
-For more details, see [bucket_io](https://github.com/eric-haibin-lin/mxnet/blob/master/example/model-parallel-lstm/lstm.py#L154).
+For more details, see [bucket_io](https://github.com/apache/incubator-mxnet/blob/master/example/rnn/old/bucket_io.py).

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