diff --git a/texar/tf/modules/encoders/hierarchical_encoders.py b/texar/tf/modules/encoders/hierarchical_encoders.py
index a3be0f9a..750d5d97 100644
--- a/texar/tf/modules/encoders/hierarchical_encoders.py
+++ b/texar/tf/modules/encoders/hierarchical_encoders.py
@@ -15,7 +15,7 @@
 Various encoders that encode data with hierarchical structure.
 """
 
-import collections
+import collections.abc
 
 import tensorflow as tf
 from tensorflow.contrib.rnn import LSTMStateTuple
@@ -256,7 +256,7 @@ def _kwargs_split(kwargs):
         if medium is None:
             states_minor = self.flatten(states_minor)
         else:
-            if not isinstance(medium, collections.Sequence):
+            if not isinstance(medium, collections.abc.Sequence):
                 medium = [medium]
             for fn in medium:
                 if isinstance(fn, str) and fn == 'flatten':
@@ -355,7 +355,7 @@ def flatten(x):
         """
         if isinstance(x, LSTMStateTuple):
             return x.h
-        if isinstance(x, collections.Sequence):
+        if isinstance(x, collections.abc.Sequence):
             return tf.concat(
                 [HierarchicalRNNEncoder.flatten(v) for v in x], -1)
         else:
diff --git a/texar/tf/utils/utils.py b/texar/tf/utils/utils.py
index 1404cc46..565df317 100644
--- a/texar/tf/utils/utils.py
+++ b/texar/tf/utils/utils.py
@@ -25,6 +25,7 @@
 from pydoc import locate
 import copy
 import collections
+import collections.abc
 import numpy as np
 
 import tensorflow as tf
@@ -577,7 +578,7 @@ def flatten_dict(dict_, parent_key="", sep="."):
     items = []
     for key, value in dict_.items():
         key_ = parent_key + sep + key if parent_key else key
-        if isinstance(value, collections.MutableMapping):
+        if isinstance(value, collections.abc.MutableMapping):
             items.extend(flatten_dict(value, key_, sep=sep).items())
         elif isinstance(value, tuple) and hasattr(value, "_asdict"):
             dict_items = collections.OrderedDict(zip(value._fields, value))