diff --git a/run_multi-task_rnn.py b/run_multi-task_rnn.py
index af8742a..e545f7a 100644
--- a/run_multi-task_rnn.py
+++ b/run_multi-task_rnn.py
@@ -226,7 +226,7 @@ def create_model(session,
         
 def train():
   print ('Applying Parameters:')
-  for k,v in FLAGS.__dict__['__flags'].iteritems():
+  for k,v in FLAGS.__flags.iteritems():
     print ('%s: %s' % (k, str(v)))
   print("Preparing data in %s" % FLAGS.data_dir)
   vocab_path = ''
diff --git a/seq_classification.py b/seq_classification.py
index 7b319b6..57f706f 100644
--- a/seq_classification.py
+++ b/seq_classification.py
@@ -12,9 +12,13 @@
 from six.moves import xrange  # pylint: disable=redefined-builtin
 # We disable pylint because we need python3 compatibility.
 import tensorflow as tf
-from tensorflow.python.ops import rnn_cell_impl
 
-linear = rnn_cell_impl._linear
+try:
+    from tensorflow.python.ops import rnn_cell_impl
+    linear = rnn_cell_impl._linear
+except AttributeError:
+    from tensorflow.contrib.rnn.python.ops.core_rnn_cell import _linear
+    linear = _linear
 
 def attention_single_output_decoder(initial_state, 
                                     attention_states,
@@ -131,4 +135,4 @@ def generate_single_output(encoder_state, attention_states, sequence_length,
       batch_size = tf.shape(targets[0])[0]
       loss = tf.reduce_sum(crossent) / tf.cast(batch_size, tf.float32)
 
-  return bucket_outputs, loss
\ No newline at end of file
+  return bucket_outputs, loss
diff --git a/seq_labeling.py b/seq_labeling.py
index 0066315..3ee6588 100644
--- a/seq_labeling.py
+++ b/seq_labeling.py
@@ -19,9 +19,12 @@
 from tensorflow.contrib.legacy_seq2seq import sequence_loss_by_example
 from tensorflow.contrib.legacy_seq2seq import sequence_loss
 
-from tensorflow.python.ops import rnn_cell_impl
-
-linear = rnn_cell_impl._linear
+try:
+    from tensorflow.python.ops import rnn_cell_impl
+    linear = rnn_cell_impl._linear
+except AttributeError:
+    from tensorflow.contrib.rnn.python.ops.core_rnn_cell import _linear
+    linear = _linear
 
 def _step(time, sequence_length, min_sequence_length, 
           max_sequence_length, zero_logit, generate_logit):