From fbc593eb02cc939a7d4a14cd4ede550f38235c3b Mon Sep 17 00:00:00 2001
From: Patrick <pn.appdev@gmail.com>
Date: Wed, 22 Feb 2017 00:28:48 +0800
Subject: [PATCH] use tf.contrib.rnn.* for TF1.0

---
 tensorlayer/layers.py | 17 ++++++++++++++---
 1 file changed, 14 insertions(+), 3 deletions(-)

diff --git a/tensorlayer/layers.py b/tensorlayer/layers.py
index 3e29ac41a..164e6bb78 100644
--- a/tensorlayer/layers.py
+++ b/tensorlayer/layers.py
@@ -4678,12 +4678,23 @@ def sampled_loss(inputs, labels):
 
         # ============ Seq Encode Layer =============
         # Create the internal multi-layer cell for our RNN.
-        single_cell = tf.nn.rnn_cell.GRUCell(size)
+        try: # TF1.0
+          single_cell = tf.contrib.rnn.GRUCell(size)
+        except:
+          single_cell = tf.nn.rnn_cell.GRUCell(size)
+
         if use_lstm:
-          single_cell = tf.nn.rnn_cell.BasicLSTMCell(size)
+          try: # TF1.0
+            single_cell = tf.contrib.rnn.BasicLSTMCell(size)
+          except:
+            single_cell = tf.nn.rnn_cell.BasicLSTMCell(size)
+
         cell = single_cell
         if num_layers > 1:
-          cell = tf.nn.rnn_cell.MultiRNNCell([single_cell] * num_layers)
+          try: # TF1.0
+            cell = tf.contrib.rnn.MultiRNNCell([single_cell] * num_layers)
+          except:
+            cell = tf.nn.rnn_cell.MultiRNNCell([single_cell] * num_layers)
 
         # ============== Seq Decode Layer ============
         # The seq2seq function: we use embedding for the input and attention.