diff --git a/tensorflow/contrib/cudnn_rnn/python/kernel_tests/cudnn_rnn_test.py b/tensorflow/contrib/cudnn_rnn/python/kernel_tests/cudnn_rnn_test.py
index be66fac66b8..5831781c2ac 100644
--- a/tensorflow/contrib/cudnn_rnn/python/kernel_tests/cudnn_rnn_test.py
+++ b/tensorflow/contrib/cudnn_rnn/python/kernel_tests/cudnn_rnn_test.py
@@ -18,7 +18,6 @@ from __future__ import division
 from __future__ import print_function
 
 import argparse
-import collections
 import functools
 import itertools
 import os
@@ -59,6 +58,7 @@ from tensorflow.python.training import momentum
 from tensorflow.python.training import rmsprop
 from tensorflow.python.training import saver as saver_lib
 from tensorflow.python.training.tracking import util as trackable_utils
+from tensorflow.python.util.compat import collections_abc
 
 
 CUDNN_LSTM = cudnn_rnn_ops.CUDNN_LSTM
@@ -1131,7 +1131,7 @@ class CudnnRNNTestTraining(test_util.TensorFlowTestCase):
     return numeric_grad.reshape(x_shape)
 
   def _GetShape(self, sess, inputs):
-    if not isinstance(inputs, collections.Iterable):
+    if not isinstance(inputs, collections_abc.Iterable):
       return sess.run(array_ops.shape(inputs))
     else:
       return sess.run([array_ops.shape(x) for x in inputs])
diff --git a/tensorflow/contrib/factorization/python/ops/factorization_ops.py b/tensorflow/contrib/factorization/python/ops/factorization_ops.py
index 5c55f7f597b..a9ce61625e2 100644
--- a/tensorflow/contrib/factorization/python/ops/factorization_ops.py
+++ b/tensorflow/contrib/factorization/python/ops/factorization_ops.py
@@ -18,7 +18,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 import numbers
 
 from six.moves import xrange  # pylint: disable=redefined-builtin
@@ -42,6 +41,7 @@ from tensorflow.python.ops import state_ops
 from tensorflow.python.ops import variable_scope
 from tensorflow.python.ops import variables
 from tensorflow.python.platform import resource_loader
+from tensorflow.python.util.compat import collections_abc
 
 _factorization_ops = loader.load_op_library(
     resource_loader.get_path_to_datafile("_factorization_ops.so"))
@@ -388,7 +388,7 @@ class WALSModel(object):
       return None
 
     init_mode = "list"
-    if isinstance(wt_init, collections.Iterable):
+    if isinstance(wt_init, collections_abc.Iterable):
       if num_shards == 1 and len(wt_init) == num_wts:
         wt_init = [wt_init]
       assert len(wt_init) == num_shards
diff --git a/tensorflow/contrib/graph_editor/util.py b/tensorflow/contrib/graph_editor/util.py
index 4b53d182f34..543c1da7e33 100644
--- a/tensorflow/contrib/graph_editor/util.py
+++ b/tensorflow/contrib/graph_editor/util.py
@@ -19,11 +19,11 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 import re
 from six import iteritems
 from tensorflow.python.framework import ops as tf_ops
 from tensorflow.python.ops import array_ops as tf_array_ops
+from tensorflow.python.util.compat import collections_abc
 
 __all__ = [
     "make_list_of_op",
@@ -157,7 +157,7 @@ def transform_tree(tree, fn, iterable_type=tuple):
         res = tree.__new__(type(tree),
                            (transform_tree(child, fn) for child in tree))
       return res
-    elif isinstance(tree, collections.Sequence):
+    elif isinstance(tree, collections_abc.Sequence):
       res = tree.__new__(type(tree))
       res.__init__(transform_tree(child, fn) for child in tree)
       return res
diff --git a/tensorflow/contrib/labeled_tensor/python/ops/_typecheck.py b/tensorflow/contrib/labeled_tensor/python/ops/_typecheck.py
index 1783a07fac9..3a257d81887 100644
--- a/tensorflow/contrib/labeled_tensor/python/ops/_typecheck.py
+++ b/tensorflow/contrib/labeled_tensor/python/ops/_typecheck.py
@@ -21,11 +21,11 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 import functools
 import re
 
 from tensorflow.python.util import tf_inspect
+from tensorflow.python.util.compat import collections_abc
 
 # used for register_type_abbreviation and _type_repr below.
 _TYPE_ABBREVIATIONS = {}
@@ -114,7 +114,7 @@ class Sequence(_SingleArgumentType):
   """
 
   def __instancecheck__(self, instance):
-    return (isinstance(instance, collections.Sequence) and
+    return (isinstance(instance, collections_abc.Sequence) and
             all(isinstance(x, self._type) for x in instance))
 
 
@@ -130,9 +130,9 @@ class Collection(_SingleArgumentType):
   """
 
   def __instancecheck__(self, instance):
-    return (isinstance(instance, collections.Iterable) and
-            isinstance(instance, collections.Sized) and
-            isinstance(instance, collections.Container) and
+    return (isinstance(instance, collections_abc.Iterable) and
+            isinstance(instance, collections_abc.Sized) and
+            isinstance(instance, collections_abc.Container) and
             all(isinstance(x, self._type) for x in instance))
 
 
@@ -157,7 +157,7 @@ class Mapping(_TwoArgumentType):
 
   def __instancecheck__(self, instance):
     key_type, value_type = self._types  # pylint: disable=unbalanced-tuple-unpacking
-    return (isinstance(instance, collections.Mapping) and
+    return (isinstance(instance, collections_abc.Mapping) and
             all(isinstance(k, key_type) for k in instance.keys()) and
             all(isinstance(k, value_type) for k in instance.values()))
 
diff --git a/tensorflow/contrib/labeled_tensor/python/ops/core.py b/tensorflow/contrib/labeled_tensor/python/ops/core.py
index b0961e5b3a2..394254cbd90 100644
--- a/tensorflow/contrib/labeled_tensor/python/ops/core.py
+++ b/tensorflow/contrib/labeled_tensor/python/ops/core.py
@@ -41,11 +41,12 @@ from tensorflow.python.framework import ops
 from tensorflow.python.framework import tensor_shape
 from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import math_ops
+from tensorflow.python.util.compat import collections_abc
 
 # pylint: disable=invalid-name
 
 # Types coercible to Axis.labels
-# We use this instead of collections.Sequence to exclude strings.
+# We use this instead of collections_abc.Sequence to exclude strings.
 LabelsLike = tc.Union(np.ndarray, range, list, tuple)
 
 # Types coercible to a tf.compat.v1.Dimension
@@ -195,7 +196,7 @@ def as_axis(axis_data):
   return axis
 
 
-class Axes(collections.Mapping):
+class Axes(collections_abc.Mapping):
   """Axis names and indices for a tensor.
 
   It is an ordered mapping, with keys given by axis name and values given
@@ -719,7 +720,7 @@ def transpose(labeled_tensor, axis_order=None, name=None):
 @tc.accepts(LabeledTensorLike,
             tc.Collection(
                 tc.Union(string_types,
-                         tc.Tuple(string_types, collections.Hashable))),
+                         tc.Tuple(string_types, collections_abc.Hashable))),
             tc.Optional(string_types))
 def expand_dims(labeled_tensor, axes, name=None):
   """Insert dimensions of size 1.
@@ -1055,7 +1056,7 @@ def align(labeled_tensor_0, labeled_tensor_1, name=None):
 
 
 @tc.returns(types.FunctionType)
-@tc.accepts(string_types, collections.Callable)
+@tc.accepts(string_types, collections_abc.Callable)
 def define_unary_op(op_name, elementwise_function):
   """Define a unary operation for labeled tensors.
 
@@ -1124,7 +1125,7 @@ sigmoid = define_unary_op('sigmoid', math_ops.sigmoid)
 
 
 @tc.returns(types.FunctionType)
-@tc.accepts(string_types, collections.Callable)
+@tc.accepts(string_types, collections_abc.Callable)
 def define_binary_op(op_name, elementwise_function):
   """Define a binary operation that broadcasts labeled tensors.
 
diff --git a/tensorflow/contrib/labeled_tensor/python/ops/ops.py b/tensorflow/contrib/labeled_tensor/python/ops/ops.py
index a04e3772799..35ab141a18f 100644
--- a/tensorflow/contrib/labeled_tensor/python/ops/ops.py
+++ b/tensorflow/contrib/labeled_tensor/python/ops/ops.py
@@ -17,7 +17,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 import types
 
 import numpy as np
@@ -34,6 +33,7 @@ from tensorflow.python.ops import math_ops
 from tensorflow.python.ops import numerics
 from tensorflow.python.ops import random_ops
 from tensorflow.python.training import input  # pylint: disable=redefined-builtin
+from tensorflow.python.util.compat import collections_abc
 
 
 @tc.returns(core.LabeledTensor)
@@ -52,7 +52,7 @@ def _gather_1d_on_axis(labeled_tensor, indexer, axis, name=None):
 @tc.returns(core.LabeledTensor)
 @tc.accepts(core.LabeledTensorLike,
             tc.Mapping(string_types,
-                       tc.Union(slice, collections.Hashable, list)),
+                       tc.Union(slice, collections_abc.Hashable, list)),
             tc.Optional(string_types))
 def select(labeled_tensor, selection, name=None):
   """Slice out a subset of the tensor.
@@ -111,8 +111,8 @@ def select(labeled_tensor, selection, name=None):
         slices[axis_name] = slice(start, stop)
 
       # Needs to be after checking for slices, since slice objects claim to be
-      # instances of collections.Hashable but hash() on them fails.
-      elif isinstance(value, collections.Hashable):
+      # instances of collections_abc.Hashable but hash() on them fails.
+      elif isinstance(value, collections_abc.Hashable):
         slices[axis_name] = axis.index(value)
 
       elif isinstance(value, list):
@@ -400,7 +400,7 @@ def rename_axis(labeled_tensor, existing_name, new_name, name=None):
 
 
 @tc.returns(tc.List(core.LabeledTensor))
-@tc.accepts(string_types, collections.Callable, int, bool,
+@tc.accepts(string_types, collections_abc.Callable, int, bool,
             tc.Collection(core.LabeledTensorLike), bool,
             tc.Optional(string_types))
 def _batch_helper(default_name,
@@ -606,7 +606,7 @@ def random_crop(labeled_tensor, shape_map, seed=None, name=None):
 
 # TODO(shoyer): Allow the user to select the axis over which to map.
 @tc.returns(core.LabeledTensor)
-@tc.accepts(collections.Callable, core.LabeledTensorLike,
+@tc.accepts(collections_abc.Callable, core.LabeledTensorLike,
             tc.Optional(string_types))
 def map_fn(fn, labeled_tensor, name=None):
   """Map on the list of tensors unpacked from labeled_tensor.
@@ -661,7 +661,7 @@ def map_fn(fn, labeled_tensor, name=None):
 
 
 @tc.returns(core.LabeledTensor)
-@tc.accepts(collections.Callable, core.LabeledTensorLike,
+@tc.accepts(collections_abc.Callable, core.LabeledTensorLike,
             core.LabeledTensorLike, tc.Optional(string_types))
 def foldl(fn, labeled_tensor, initial_value, name=None):
   """Left fold on the list of tensors unpacked from labeled_tensor.
@@ -754,7 +754,7 @@ def squeeze(labeled_tensor, axis_names=None, name=None):
 
 # pylint: disable=invalid-name
 ReduceAxis = tc.Union(string_types,
-                      tc.Tuple(string_types, collections.Hashable))
+                      tc.Tuple(string_types, collections_abc.Hashable))
 ReduceAxes = tc.Optional(tc.Union(ReduceAxis, tc.Collection(ReduceAxis)))
 # pylint: enable=invalid-name
 
@@ -876,7 +876,7 @@ def matmul(a, b, name=None):
 
 
 @tc.returns(types.FunctionType)
-@tc.accepts(string_types, collections.Callable)
+@tc.accepts(string_types, collections_abc.Callable)
 def define_reduce_op(op_name, reduce_fn):
   """Define a reduction op for labeled tensors.
 
diff --git a/tensorflow/contrib/layers/python/layers/feature_column.py b/tensorflow/contrib/layers/python/layers/feature_column.py
index e47a52a7072..385dcc0d80a 100644
--- a/tensorflow/contrib/layers/python/layers/feature_column.py
+++ b/tensorflow/contrib/layers/python/layers/feature_column.py
@@ -155,6 +155,7 @@ from tensorflow.python.ops import variables
 from tensorflow.python.platform import tf_logging as logging
 from tensorflow.python.util import deprecation
 from tensorflow.python.util import nest
+from tensorflow.python.util.compat import collections_abc
 
 # Imports the core `InputLayer` symbol in contrib during development.
 InputLayer = fc_core.InputLayer  # pylint: disable=invalid-name
@@ -1403,7 +1404,7 @@ def shared_embedding_columns(sparse_id_columns,
       least one element of `sparse_id_columns` is not a `SparseColumn` or a
       `WeightedSparseColumn`.
   """
-  if (not isinstance(sparse_id_columns, collections.Sequence) or
+  if (not isinstance(sparse_id_columns, collections_abc.Sequence) or
       isinstance(sparse_id_columns, six.string_types)):
     raise TypeError(
         "sparse_id_columns must be a non-string sequence (ex: list or tuple) "
diff --git a/tensorflow/contrib/learn/python/learn/estimators/_sklearn.py b/tensorflow/contrib/learn/python/learn/estimators/_sklearn.py
index 99f22d182cd..a15bbce515b 100644
--- a/tensorflow/contrib/learn/python/learn/estimators/_sklearn.py
+++ b/tensorflow/contrib/learn/python/learn/estimators/_sklearn.py
@@ -19,12 +19,13 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 import os
 
 import numpy as np
 import six
 
+from tensorflow.python.util.compat import collections_abc
+
 
 def _pprint(d):
   return ', '.join(['%s=%s' % (key, str(value)) for key, value in d.items()])
@@ -55,7 +56,7 @@ class _BaseEstimator(object):
     for key in param_names:
       value = getattr(self, key, None)
 
-      if isinstance(value, collections.Callable):
+      if isinstance(value, collections_abc.Callable):
         continue
 
       # XXX: should we rather test if instance of estimator?
diff --git a/tensorflow/contrib/tensor_forest/hybrid/python/hybrid_model.py b/tensorflow/contrib/tensor_forest/hybrid/python/hybrid_model.py
index 926e4dda916..a8a5b574691 100644
--- a/tensorflow/contrib/tensor_forest/hybrid/python/hybrid_model.py
+++ b/tensorflow/contrib/tensor_forest/hybrid/python/hybrid_model.py
@@ -17,8 +17,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
-
 from tensorflow.contrib import layers
 from tensorflow.contrib.framework.python.ops import variables as framework_variables
 
@@ -29,6 +27,7 @@ from tensorflow.python.ops import nn_ops
 from tensorflow.python.ops import variables
 
 from tensorflow.python.training import adagrad
+from tensorflow.python.util.compat import collections_abc
 
 
 class HybridModel(object):
@@ -66,7 +65,7 @@ class HybridModel(object):
 
     # If this is a collection of layers, return the mean of their inference
     # results.
-    if isinstance(layer, collections.Iterable):
+    if isinstance(layer, collections_abc.Iterable):
       return math_ops.reduce_mean(
           array_ops.stack([l.inference_graph(data) for l in layer]), 0)
     # If this is a single layer, return its inference result.
diff --git a/tensorflow/python/client/session.py b/tensorflow/python/client/session.py
index 820c7d8b1f6..5f98be745bf 100644
--- a/tensorflow/python/client/session.py
+++ b/tensorflow/python/client/session.py
@@ -18,7 +18,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 import functools
 import re
 import threading
@@ -41,6 +40,7 @@ from tensorflow.python.training.experimental import mixed_precision_global_state
 from tensorflow.python.util import compat
 from tensorflow.python.util import nest
 from tensorflow.python.util.tf_export import tf_export
+from tensorflow.python.util.compat import collections_abc
 
 
 class SessionInterface(object):
@@ -259,7 +259,7 @@ class _FetchMapper(object):
     elif isinstance(fetch, (list, tuple)):
       # NOTE(touts): This is also the code path for namedtuples.
       return _ListFetchMapper(fetch)
-    elif isinstance(fetch, collections.Mapping):
+    elif isinstance(fetch, collections_abc.Mapping):
       return _DictFetchMapper(fetch)
     elif _is_attrs_instance(fetch):
       return _AttrsFetchMapper(fetch)
diff --git a/tensorflow/python/data/experimental/ops/scan_ops.py b/tensorflow/python/data/experimental/ops/scan_ops.py
index a81f5e64fee..e40d229b54a 100644
--- a/tensorflow/python/data/experimental/ops/scan_ops.py
+++ b/tensorflow/python/data/experimental/ops/scan_ops.py
@@ -17,14 +17,13 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
-
 from tensorflow.python.compat import compat
 from tensorflow.python.data.ops import dataset_ops
 from tensorflow.python.data.util import nest
 from tensorflow.python.data.util import structure
 from tensorflow.python.framework import ops
 from tensorflow.python.ops import gen_experimental_dataset_ops
+from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.tf_export import tf_export
 
 
@@ -53,7 +52,7 @@ class _ScanDataset(dataset_ops.UnaryDataset):
                            input_dataset.element_spec),
           add_to_graph=False)
       if not (
-          isinstance(wrapped_func.output_types, collections.Sequence) and
+          isinstance(wrapped_func.output_types, collections_abc.Sequence) and
           len(wrapped_func.output_types) == 2):
         raise TypeError("The scan function must return a pair comprising the "
                         "new state and the output value.")
diff --git a/tensorflow/python/data/util/nest.py b/tensorflow/python/data/util/nest.py
index ebfd8af3423..851ac5eab68 100644
--- a/tensorflow/python/data/util/nest.py
+++ b/tensorflow/python/data/util/nest.py
@@ -35,12 +35,11 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections as _collections
-
 import six as _six
 
 from tensorflow.python import pywrap_tensorflow as _pywrap_tensorflow
 from tensorflow.python.framework import sparse_tensor as _sparse_tensor
+from tensorflow.python.util.compat import collections_abc as _collections_abc
 
 
 def _sorted(dict_):
@@ -71,7 +70,7 @@ def _sequence_like(instance, args):
     return type(instance)((key, result[key]) for key in instance)
   elif (isinstance(instance, tuple) and
         hasattr(instance, "_fields") and
-        isinstance(instance._fields, _collections.Sequence) and
+        isinstance(instance._fields, _collections_abc.Sequence) and
         all(isinstance(f, _six.string_types) for f in instance._fields)):
     # This is a namedtuple
     return type(instance)(*args)
diff --git a/tensorflow/python/distribute/multi_worker_test_base.py b/tensorflow/python/distribute/multi_worker_test_base.py
index c5c87fd31d1..04fa0fb7fda 100644
--- a/tensorflow/python/distribute/multi_worker_test_base.py
+++ b/tensorflow/python/distribute/multi_worker_test_base.py
@@ -18,7 +18,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 import contextlib
 import copy
 import json
@@ -50,6 +49,7 @@ from tensorflow.python.platform import tf_logging as logging
 from tensorflow.python.training import coordinator
 from tensorflow.python.training import server_lib
 from tensorflow.python.util import nest
+from tensorflow.python.util.compat import collections_abc
 
 
 original_run_std_server = dc._run_std_server  # pylint: disable=protected-access
@@ -353,7 +353,7 @@ class MultiWorkerTestBase(test.TestCase):
     self.assertEqual(self._result, len(threads))
 
 
-class MockOsEnv(collections.Mapping):
+class MockOsEnv(collections_abc.Mapping):
   """A class that allows per-thread TF_CONFIG."""
 
   def __init__(self, *args):
diff --git a/tensorflow/python/feature_column/feature_column.py b/tensorflow/python/feature_column/feature_column.py
index cf3043ec7bb..a5c3bf6491f 100644
--- a/tensorflow/python/feature_column/feature_column.py
+++ b/tensorflow/python/feature_column/feature_column.py
@@ -166,6 +166,7 @@ from tensorflow.python.platform import tf_logging as logging
 from tensorflow.python.training import checkpoint_utils
 from tensorflow.python.util import nest
 from tensorflow.python.util.tf_export import tf_export
+from tensorflow.python.util.compat import collections_abc
 
 
 def _internal_input_layer(features,
@@ -2245,7 +2246,7 @@ def _normalize_feature_columns(feature_columns):
   if isinstance(feature_columns, _FeatureColumn):
     feature_columns = [feature_columns]
 
-  if isinstance(feature_columns, collections.Iterator):
+  if isinstance(feature_columns, collections_abc.Iterator):
     feature_columns = list(feature_columns)
 
   if isinstance(feature_columns, dict):
diff --git a/tensorflow/python/feature_column/feature_column_v2.py b/tensorflow/python/feature_column/feature_column_v2.py
index a9d0fa2e906..a492d90a661 100644
--- a/tensorflow/python/feature_column/feature_column_v2.py
+++ b/tensorflow/python/feature_column/feature_column_v2.py
@@ -169,6 +169,7 @@ from tensorflow.python.util import deprecation
 from tensorflow.python.util import nest
 from tensorflow.python.util.tf_export import keras_export
 from tensorflow.python.util.tf_export import tf_export
+from tensorflow.python.util.compat import collections_abc
 
 
 _FEATURE_COLUMN_DEPRECATION_DATE = None
@@ -2740,7 +2741,7 @@ def _normalize_feature_columns(feature_columns):
   if isinstance(feature_columns, FeatureColumn):
     feature_columns = [feature_columns]
 
-  if isinstance(feature_columns, collections.Iterator):
+  if isinstance(feature_columns, collections_abc.Iterator):
     feature_columns = list(feature_columns)
 
   if isinstance(feature_columns, dict):
diff --git a/tensorflow/python/framework/ops.py b/tensorflow/python/framework/ops.py
index 070ce32a95a..8b3b0b6c079 100644
--- a/tensorflow/python/framework/ops.py
+++ b/tensorflow/python/framework/ops.py
@@ -65,6 +65,7 @@ from tensorflow.python.util import lock_util
 from tensorflow.python.util import memory
 from tensorflow.python.util import tf_contextlib
 from tensorflow.python.util import tf_stack
+from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.deprecation import deprecated_args
 from tensorflow.python.util.tf_export import tf_export
 
@@ -1234,7 +1235,7 @@ def internal_convert_n_to_tensor(values,
     RuntimeError: If a registered conversion function returns an invalid
       value.
   """
-  if not isinstance(values, collections.Sequence):
+  if not isinstance(values, collections_abc.Sequence):
     raise TypeError("values must be a sequence.")
   ret = []
   if ctx is None:
@@ -1371,7 +1372,7 @@ def internal_convert_n_to_tensor_or_composite(values,
     RuntimeError: If a registered conversion function returns an invalid
       value.
   """
-  if not isinstance(values, collections.Sequence):
+  if not isinstance(values, collections_abc.Sequence):
     raise TypeError("values must be a sequence.")
   ret = []
   for i, value in enumerate(values):
diff --git a/tensorflow/python/framework/test_util.py b/tensorflow/python/framework/test_util.py
index a1adf18bf35..6bbaf05e7e1 100644
--- a/tensorflow/python/framework/test_util.py
+++ b/tensorflow/python/framework/test_util.py
@@ -19,7 +19,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 from collections import OrderedDict
 import contextlib
 import functools
@@ -83,6 +82,7 @@ from tensorflow.python.util import tf_decorator
 from tensorflow.python.util import tf_inspect
 from tensorflow.python.util.protobuf import compare
 from tensorflow.python.util.tf_export import tf_export
+from tensorflow.python.util.compat import collections_abc
 
 
 # If the below import is made available through the BUILD rule, then this
@@ -2301,8 +2301,8 @@ class TensorFlowTestCase(googletest.TestCase):
       a = a._asdict()
     if hasattr(b, "_asdict"):
       b = b._asdict()
-    a_is_dict = isinstance(a, collections.Mapping)
-    if a_is_dict != isinstance(b, collections.Mapping):
+    a_is_dict = isinstance(a, collections_abc.Mapping)
+    if a_is_dict != isinstance(b, collections_abc.Mapping):
       raise ValueError("Can't compare dict to non-dict, a%s vs b%s. %s" %
                        (path_str, path_str, msg))
     if a_is_dict:
diff --git a/tensorflow/python/keras/callbacks.py b/tensorflow/python/keras/callbacks.py
index c735f71245e..8de90df739a 100644
--- a/tensorflow/python/keras/callbacks.py
+++ b/tensorflow/python/keras/callbacks.py
@@ -47,6 +47,7 @@ from tensorflow.python.ops import summary_ops_v2
 from tensorflow.python.platform import tf_logging as logging
 from tensorflow.python.training import checkpoint_management
 from tensorflow.python.util.tf_export import keras_export
+from tensorflow.python.util.compat import collections_abc
 
 try:
   import requests
@@ -1902,7 +1903,7 @@ class CSVLogger(Callback):
       is_zero_dim_ndarray = isinstance(k, np.ndarray) and k.ndim == 0
       if isinstance(k, six.string_types):
         return k
-      elif isinstance(k, collections.Iterable) and not is_zero_dim_ndarray:
+      elif isinstance(k, collections_abc.Iterable) and not is_zero_dim_ndarray:
         return '"[%s]"' % (', '.join(map(str, k)))
       else:
         return k
diff --git a/tensorflow/python/keras/engine/training.py b/tensorflow/python/keras/engine/training.py
index 584ec1a8a0e..976fd4e7956 100644
--- a/tensorflow/python/keras/engine/training.py
+++ b/tensorflow/python/keras/engine/training.py
@@ -63,6 +63,7 @@ from tensorflow.python.util import nest
 from tensorflow.python.util import serialization
 from tensorflow.python.util import tf_inspect
 from tensorflow.python.util.tf_export import keras_export
+from tensorflow.python.util.compat import collections_abc
 
 try:
   from scipy.sparse import issparse  # pylint: disable=g-import-not-at-top
@@ -603,9 +604,9 @@ class Model(network.Network):
             or a dataset iterator, and 'validation_steps' is None, validation
             will run until the `validation_data` dataset is exhausted.
         validation_freq: Only relevant if validation data is provided. Integer
-            or `collections.Container` instance (e.g. list, tuple, etc.). If an
-            integer, specifies how many training epochs to run before a new
-            validation run is performed, e.g. `validation_freq=2` runs
+            or `collections_abc.Container` instance (e.g. list, tuple, etc.).
+            If an integer, specifies how many training epochs to run before a
+            new validation run is performed, e.g. `validation_freq=2` runs
             validation every 2 epochs. If a Container, specifies the epochs on
             which to run validation, e.g. `validation_freq=[1, 2, 10]` runs
             validation at the end of the 1st, 2nd, and 10th epochs.
@@ -1048,7 +1049,7 @@ class Model(network.Network):
     # at this point.
     if self.run_eagerly or self._distribution_strategy:
       inputs = training_utils.cast_if_floating_dtype(inputs)
-      if isinstance(inputs, collections.Sequence):
+      if isinstance(inputs, collections_abc.Sequence):
         # Unwrap lists with only one input, as we do when training on batch
         if len(inputs) == 1:
           inputs = inputs[0]
@@ -1126,9 +1127,9 @@ class Model(network.Network):
             Optional for `Sequence`: if unspecified, will use
             the `len(validation_data)` as a number of steps.
         validation_freq: Only relevant if validation data is provided. Integer
-            or `collections.Container` instance (e.g. list, tuple, etc.). If an
-            integer, specifies how many training epochs to run before a new
-            validation run is performed, e.g. `validation_freq=2` runs
+            or `collections_abc.Container` instance (e.g. list, tuple, etc.).
+            If an integer, specifies how many training epochs to run before a
+            new validation run is performed, e.g. `validation_freq=2` runs
             validation every 2 epochs. If a Container, specifies the epochs on
             which to run validation, e.g. `validation_freq=[1, 2, 10]` runs
             validation at the end of the 1st, 2nd, and 10th epochs.
diff --git a/tensorflow/python/keras/engine/training_arrays.py b/tensorflow/python/keras/engine/training_arrays.py
index bc8944a0a08..90edfcd48a3 100644
--- a/tensorflow/python/keras/engine/training_arrays.py
+++ b/tensorflow/python/keras/engine/training_arrays.py
@@ -90,9 +90,10 @@ def model_iteration(model,
         declaring one epoch finished and starting the next epoch. Ignored with
         the default value of `None`.
       validation_steps: Number of steps to run validation for (only if doing
-        validation from data tensors). Ignored with the default value of `None`.
+        validation from data tensors). Ignored with the default value of
+        `None`.
       validation_freq: Only relevant if validation data is provided. Integer or
-        `collections.Container` instance (e.g. list, tuple, etc.). If an
+        `collections_abc.Container` instance (e.g. list, tuple, etc.). If an
         integer, specifies how many training epochs to run before a new
         validation run is performed, e.g. `validation_freq=2` runs
         validation every 2 epochs. If a Container, specifies the epochs on
@@ -100,8 +101,8 @@ def model_iteration(model,
         validation at the end of the 1st, 2nd, and 10th epochs.
       mode: One of ModeKeys.TRAIN/ModeKeys.TEST/ModeKeys.PREDICT.
       validation_in_fit: if true, then this method is invoked from within
-        training iteration (for validation). In the case where `val_inputs` is a
-        dataset, this flag indicates that its iterator and feed values are
+        training iteration (for validation). In the case where `val_inputs` is
+        a dataset, this flag indicates that its iterator and feed values are
         already created so should properly reuse resources.
       prepared_feed_values_from_dataset: if True, `inputs` is a list of feed
         tensors returned from `_prepare_feed_values` call on the validation
diff --git a/tensorflow/python/keras/engine/training_distributed.py b/tensorflow/python/keras/engine/training_distributed.py
index 18851d5ee0c..8e8aac913cd 100644
--- a/tensorflow/python/keras/engine/training_distributed.py
+++ b/tensorflow/python/keras/engine/training_distributed.py
@@ -149,7 +149,7 @@ def experimental_tpu_fit_loop(model,
           (only if doing validation from data tensors).
           Ignored with the default value of `None`.
       validation_freq: Only relevant if validation data is provided. Integer or
-          `collections.Container` instance (e.g. list, tuple, etc.). If an
+          `collections.abc.Container` instance (e.g. list, tuple, etc.). If an
           integer, specifies how many training epochs to run before a new
           validation run is performed, e.g. `validation_freq=2` runs
           validation every 2 epochs. If a Container, specifies the epochs on
diff --git a/tensorflow/python/keras/engine/training_eager.py b/tensorflow/python/keras/engine/training_eager.py
index 41ce12caf37..32ac4e37197 100644
--- a/tensorflow/python/keras/engine/training_eager.py
+++ b/tensorflow/python/keras/engine/training_eager.py
@@ -19,8 +19,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
-
 import numpy as np
 
 from tensorflow.python.eager.backprop import GradientTape
@@ -34,6 +32,7 @@ from tensorflow.python.ops import math_ops
 from tensorflow.python.ops.losses import util as tf_losses_utils
 from tensorflow.python.platform import tf_logging as logging
 from tensorflow.python.util import nest
+from tensorflow.python.util.compat import collections_abc
 
 
 def _eager_loss_fn(outputs, targets, loss_fn, output_name):
@@ -275,7 +274,7 @@ def train_on_batch(model,
   Returns:
       total loss and the loss associated with each output.
   """
-  if isinstance(inputs, collections.Sequence):
+  if isinstance(inputs, collections_abc.Sequence):
     if len(inputs) and tensor_util.is_tensor(inputs[0]):
       inputs = training_utils.cast_if_floating_to_model_input_dtypes(inputs,
                                                                      model)
@@ -334,7 +333,7 @@ def test_on_batch(model,
   Returns:
       total loss, loss and metrics associated with each output.
   """
-  if isinstance(inputs, collections.Sequence):
+  if isinstance(inputs, collections_abc.Sequence):
     if len(inputs) and tensor_util.is_tensor(inputs[0]):
       inputs = training_utils.cast_if_floating_to_model_input_dtypes(inputs,
                                                                      model)
diff --git a/tensorflow/python/keras/engine/training_generator.py b/tensorflow/python/keras/engine/training_generator.py
index 51368098074..8d942114240 100644
--- a/tensorflow/python/keras/engine/training_generator.py
+++ b/tensorflow/python/keras/engine/training_generator.py
@@ -80,7 +80,7 @@ def model_iteration(model,
       validation_steps: Total number of steps (batches of samples) before
         declaring validation finished.
       validation_freq: Only relevant if validation data is provided. Integer or
-        `collections.Container` instance (e.g. list, tuple, etc.). If an
+        `collections.abc.Container` instance (e.g. list, tuple, etc.). If an
         integer, specifies how many training epochs to run before a new
         validation run is performed, e.g. `validation_freq=2` runs
         validation every 2 epochs. If a Container, specifies the epochs on
diff --git a/tensorflow/python/keras/engine/training_utils.py b/tensorflow/python/keras/engine/training_utils.py
index 8f5c830d6e9..80ae601361a 100644
--- a/tensorflow/python/keras/engine/training_utils.py
+++ b/tensorflow/python/keras/engine/training_utils.py
@@ -53,6 +53,7 @@ from tensorflow.python.ops import math_ops
 from tensorflow.python.ops.losses import util as tf_losses_utils
 from tensorflow.python.platform import tf_logging as logging
 from tensorflow.python.util import nest
+from tensorflow.python.util.compat import collections_abc
 
 
 @six.add_metaclass(abc.ABCMeta)
@@ -1025,7 +1026,7 @@ def get_loss_function(loss):
     return loss
 
   # Deserialize loss configuration, if needed.
-  if isinstance(loss, collections.Mapping):
+  if isinstance(loss, collections_abc.Mapping):
     loss = losses.get(loss)
 
   # Custom callable class.
@@ -1245,7 +1246,7 @@ def prepare_loss_functions(loss, output_names):
       ValueError: If loss is a dict with keys not in model output names,
           or if loss is a list with len not equal to model outputs.
   """
-  if isinstance(loss, collections.Mapping):
+  if isinstance(loss, collections_abc.Mapping):
     generic_utils.check_for_unexpected_keys('loss', loss, output_names)
     loss_functions = []
     for name in output_names:
@@ -1257,7 +1258,7 @@ def prepare_loss_functions(loss, output_names):
       loss_functions.append(get_loss_function(loss.get(name, None)))
   elif isinstance(loss, six.string_types):
     loss_functions = [get_loss_function(loss) for _ in output_names]
-  elif isinstance(loss, collections.Sequence):
+  elif isinstance(loss, collections_abc.Sequence):
     if len(loss) != len(output_names):
       raise ValueError('When passing a list as loss, it should have one entry '
                        'per model outputs. The model has {} outputs, but you '
@@ -1747,9 +1748,9 @@ def should_run_validation(validation_freq, epoch):
       raise ValueError('`validation_freq` can not be less than 1.')
     return one_indexed_epoch % validation_freq == 0
 
-  if not isinstance(validation_freq, collections.Container):
+  if not isinstance(validation_freq, collections_abc.Container):
     raise ValueError('`validation_freq` must be an Integer or '
-                     '`collections.Container` (e.g. list, tuple, etc.)')
+                     '`collections_abc.Container` (e.g. list, tuple, etc.)')
   return one_indexed_epoch in validation_freq
 
 
diff --git a/tensorflow/python/keras/keras_parameterized.py b/tensorflow/python/keras/keras_parameterized.py
index 0b6beb8ddcc..e48e3fd7456 100644
--- a/tensorflow/python/keras/keras_parameterized.py
+++ b/tensorflow/python/keras/keras_parameterized.py
@@ -18,7 +18,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 import functools
 import itertools
 import unittest
@@ -31,6 +30,7 @@ from tensorflow.python.eager import context
 from tensorflow.python.keras import testing_utils
 from tensorflow.python.platform import test
 from tensorflow.python.util import nest
+from tensorflow.python.util.compat import collections_abc
 
 
 class TestCase(test.TestCase, parameterized.TestCase):
@@ -312,7 +312,7 @@ def _test_or_class_decorator(test_or_class, single_method_decorator):
     The decorated result.
   """
   def _decorate_test_or_class(obj):
-    if isinstance(obj, collections.Iterable):
+    if isinstance(obj, collections_abc.Iterable):
       return itertools.chain.from_iterable(
           single_method_decorator(method) for method in obj)
     if isinstance(obj, type):
diff --git a/tensorflow/python/kernel_tests/conv_ops_3d_test.py b/tensorflow/python/kernel_tests/conv_ops_3d_test.py
index deb465a0474..366c3c08295 100644
--- a/tensorflow/python/kernel_tests/conv_ops_3d_test.py
+++ b/tensorflow/python/kernel_tests/conv_ops_3d_test.py
@@ -18,7 +18,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 import math
 
 import numpy as np
@@ -33,6 +32,7 @@ from tensorflow.python.ops import nn_ops
 import tensorflow.python.ops.nn_grad  # pylint: disable=unused-import
 from tensorflow.python.platform import test
 from tensorflow.python.framework import test_util
+from tensorflow.python.util.compat import collections_abc
 
 
 def GetTestConfigs():
@@ -79,7 +79,7 @@ class Conv3DTest(test.TestCase):
       t1 = constant_op.constant(x1, shape=tensor_in_sizes, dtype=dtype)
       t2 = constant_op.constant(x2, shape=filter_in_sizes, dtype=dtype)
 
-      if isinstance(stride, collections.Iterable):
+      if isinstance(stride, collections_abc.Iterable):
         strides = [1] + list(stride) + [1]
       else:
         strides = [1, stride, stride, stride, 1]
@@ -137,7 +137,7 @@ class Conv3DTest(test.TestCase):
     with self.cached_session(use_gpu=use_gpu):
       t1 = constant_op.constant(x1, shape=tensor_in_sizes)
       t2 = constant_op.constant(x2, shape=filter_in_sizes)
-      if isinstance(stride, collections.Iterable):
+      if isinstance(stride, collections_abc.Iterable):
         strides = list(stride)
       else:
         strides = [stride, stride, stride]
@@ -377,7 +377,7 @@ class Conv3DTest(test.TestCase):
         filter_planes, filter_rows, filter_cols, in_depth, out_depth
     ]
 
-    if isinstance(stride, collections.Iterable):
+    if isinstance(stride, collections_abc.Iterable):
       strides = [1] + list(stride) + [1]
     else:
       strides = [1, stride, stride, stride, 1]
diff --git a/tensorflow/python/kernel_tests/conv_ops_test.py b/tensorflow/python/kernel_tests/conv_ops_test.py
index ccc0ab8c023..51c004b14a6 100644
--- a/tensorflow/python/kernel_tests/conv_ops_test.py
+++ b/tensorflow/python/kernel_tests/conv_ops_test.py
@@ -18,7 +18,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 import os
 import time
 
@@ -47,6 +46,7 @@ from tensorflow.python.ops import variables
 import tensorflow.python.ops.nn_grad  # pylint: disable=unused-import
 from tensorflow.python.platform import test
 from tensorflow.python.platform import tf_logging
+from tensorflow.python.util.compat import collections_abc
 
 
 def GetShrunkInceptionShapes(shrink=10):
@@ -266,7 +266,7 @@ class Conv2DTest(test.TestCase):
     with test_util.device(use_gpu):
       t1 = constant_op.constant(x1, shape=tensor_in_sizes)
       t2 = constant_op.constant(x2, shape=filter_in_sizes)
-      if isinstance(stride, collections.Iterable):
+      if isinstance(stride, collections_abc.Iterable):
         strides = list(stride)
       else:
         strides = [stride, stride]
diff --git a/tensorflow/python/ops/clip_ops.py b/tensorflow/python/ops/clip_ops.py
index a247a33c10d..88b0fdd6da3 100644
--- a/tensorflow/python/ops/clip_ops.py
+++ b/tensorflow/python/ops/clip_ops.py
@@ -18,8 +18,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
-
 import six
 
 from tensorflow.python.framework import constant_op
@@ -31,6 +29,7 @@ from tensorflow.python.ops import gen_nn_ops
 from tensorflow.python.ops import math_ops
 from tensorflow.python.util import deprecation
 from tensorflow.python.util import dispatch
+from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.tf_export import tf_export
 
 
@@ -49,14 +48,14 @@ def clip_by_value(t, clip_value_min, clip_value_max,
   correct results.
 
   For example:
-  
+
   ```python
   A = tf.constant([[1, 20, 13], [3, 21, 13]])
   B = tf.clip_by_value(A, clip_value_min=0, clip_value_max=3) # [[1, 3, 3],[3, 3, 3]]
-  C = tf.clip_by_value(A, clip_value_min=0., clip_value_max=3.) # throws `TypeError` 
+  C = tf.clip_by_value(A, clip_value_min=0., clip_value_max=3.) # throws `TypeError`
   as input and clip_values are of different dtype
   ```
-  
+
   Args:
     t: A `Tensor` or `IndexedSlices`.
     clip_value_min: A 0-D (scalar) `Tensor`, or a `Tensor` with the same shape
@@ -71,8 +70,8 @@ def clip_by_value(t, clip_value_min, clip_value_max,
   Raises:
     ValueError: If the clip tensors would trigger array broadcasting
       that would make the returned tensor larger than the input.
-    TypeError: If dtype of the input is `int32` and dtype of 
-    the `clip_value_min' or `clip_value_max` is `float32`  
+    TypeError: If dtype of the input is `int32` and dtype of
+    the `clip_value_min' or `clip_value_max` is `float32`
   """
   with ops.name_scope(name, "clip_by_value",
                       [t, clip_value_min, clip_value_max]) as name:
@@ -208,7 +207,7 @@ def global_norm(t_list, name=None):
   Raises:
     TypeError: If `t_list` is not a sequence.
   """
-  if (not isinstance(t_list, collections.Sequence)
+  if (not isinstance(t_list, collections_abc.Sequence)
       or isinstance(t_list, six.string_types)):
     raise TypeError("t_list should be a sequence")
   t_list = list(t_list)
@@ -282,7 +281,7 @@ def clip_by_global_norm(t_list, clip_norm, use_norm=None, name=None):
   Raises:
     TypeError: If `t_list` is not a sequence.
   """
-  if (not isinstance(t_list, collections.Sequence)
+  if (not isinstance(t_list, collections_abc.Sequence)
       or isinstance(t_list, six.string_types)):
     raise TypeError("t_list should be a sequence")
   t_list = list(t_list)
diff --git a/tensorflow/python/ops/data_flow_ops.py b/tensorflow/python/ops/data_flow_ops.py
index 9c49fc85270..e719e07170a 100644
--- a/tensorflow/python/ops/data_flow_ops.py
+++ b/tensorflow/python/ops/data_flow_ops.py
@@ -18,7 +18,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 import hashlib
 import threading
 
@@ -41,6 +40,7 @@ from tensorflow.python.ops import resource_variable_ops
 # pylint: disable=wildcard-import
 from tensorflow.python.ops.gen_data_flow_ops import *
 from tensorflow.python.util import deprecation
+from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.tf_export import tf_export
 
 # pylint: enable=wildcard-import
@@ -64,7 +64,7 @@ def _as_shape_list(shapes,
   """Convert shapes to a list of tuples of int (or None)."""
   del dtypes
   if unknown_dim_allowed:
-    if (not isinstance(shapes, collections.Sequence) or not shapes or
+    if (not isinstance(shapes, collections_abc.Sequence) or not shapes or
         any(shape is None or isinstance(shape, int) for shape in shapes)):
       raise ValueError(
           "When providing partial shapes, a list of shapes must be provided.")
diff --git a/tensorflow/python/ops/gradients_util.py b/tensorflow/python/ops/gradients_util.py
index 84a21d0bab5..5ceeb5376ec 100644
--- a/tensorflow/python/ops/gradients_util.py
+++ b/tensorflow/python/ops/gradients_util.py
@@ -43,6 +43,7 @@ from tensorflow.python.ops import resource_variable_ops
 from tensorflow.python.ops.unconnected_gradients import UnconnectedGradients
 from tensorflow.python.platform import tf_logging as logging
 from tensorflow.python.util import compat
+from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.tf_export import tf_export
 
 
@@ -728,7 +729,7 @@ def _HasAnyNotNoneGrads(grads, op):
   for out_grad in out_grads:
     if isinstance(out_grad, (ops.Tensor, ops.IndexedSlices)):
       return True
-    if out_grad and isinstance(out_grad, collections.Sequence):
+    if out_grad and isinstance(out_grad, collections_abc.Sequence):
       if any(g is not None for g in out_grad):
         return True
   return False
@@ -953,7 +954,7 @@ def _AggregatedGrads(grads,
         assert control_flow_util.IsLoopSwitch(op)
         continue
     # Grads have to be Tensors or IndexedSlices
-    if (isinstance(out_grad, collections.Sequence) and not all(
+    if (isinstance(out_grad, collections_abc.Sequence) and not all(
         isinstance(g, (ops.Tensor, ops.IndexedSlices))
         for g in out_grad
         if g is not None
diff --git a/tensorflow/python/ops/nn_ops.py b/tensorflow/python/ops/nn_ops.py
index 418a34fce50..9878bf0366d 100644
--- a/tensorflow/python/ops/nn_ops.py
+++ b/tensorflow/python/ops/nn_ops.py
@@ -42,6 +42,7 @@ from tensorflow.python.ops.gen_nn_ops import *
 # pylint: enable=wildcard-import
 from tensorflow.python.platform import tf_logging as logging
 from tensorflow.python.util import deprecation
+from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.deprecation import deprecated_args
 from tensorflow.python.util.deprecation import deprecated_argument_lookup
 
@@ -57,7 +58,7 @@ def _get_sequence(value, n, channel_index, name):
   """Formats a value input for gen_nn_ops."""
   if value is None:
     value = [1]
-  elif not isinstance(value, collections.Sized):
+  elif not isinstance(value, collections_abc.Sized):
     value = [value]
 
   current_n = len(value)
@@ -2742,7 +2743,7 @@ def relu6(features, name=None):
 def leaky_relu(features, alpha=0.2, name=None):
   """Compute the Leaky ReLU activation function.
 
-  Source: [Rectifier Nonlinearities Improve Neural Network Acoustic Models. 
+  Source: [Rectifier Nonlinearities Improve Neural Network Acoustic Models.
   AL Maas, AY Hannun, AY Ng - Proc. ICML, 2013](https://ai.stanford.edu/~amaas/papers/relu_hybrid_icml2013_final.pdf).
 
   Args:
diff --git a/tensorflow/python/ops/sparse_ops.py b/tensorflow/python/ops/sparse_ops.py
index f6b26c80a10..bf38c3c0f9b 100644
--- a/tensorflow/python/ops/sparse_ops.py
+++ b/tensorflow/python/ops/sparse_ops.py
@@ -23,7 +23,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 import numbers
 
 import numpy as np
@@ -46,6 +45,7 @@ from tensorflow.python.util import compat
 from tensorflow.python.util import deprecation
 from tensorflow.python.util import dispatch
 from tensorflow.python.util import tf_inspect
+from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.tf_export import get_canonical_name_for_symbol
 from tensorflow.python.util.tf_export import tf_export
 
@@ -1658,10 +1658,10 @@ def sparse_merge_impl(sp_ids,
                       type(vocab_size))
     vocab_size = [vocab_size]
   else:
-    if not isinstance(sp_ids, collections.Iterable):
+    if not isinstance(sp_ids, collections_abc.Iterable):
       raise TypeError("sp_ids has to be a SparseTensor or list thereof. "
                       "Found %s" % type(sp_ids))
-    if not isinstance(vocab_size, collections.Iterable):
+    if not isinstance(vocab_size, collections_abc.Iterable):
       raise TypeError("vocab_size has to be a list of Tensors or Python ints. "
                       "Found %s" % type(vocab_size))
     for dim in vocab_size:
diff --git a/tensorflow/python/saved_model/model_utils/mode_keys.py b/tensorflow/python/saved_model/model_utils/mode_keys.py
index 2912de7210f..6f7a787befa 100644
--- a/tensorflow/python/saved_model/model_utils/mode_keys.py
+++ b/tensorflow/python/saved_model/model_utils/mode_keys.py
@@ -19,7 +19,7 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
+from tensorflow.python.util.compat import collections_abc
 
 
 class KerasModeKeys(object):
@@ -65,7 +65,7 @@ def is_train(mode):
   return mode in [KerasModeKeys.TRAIN, EstimatorModeKeys.TRAIN]
 
 
-class ModeKeyMap(collections.Mapping):
+class ModeKeyMap(collections_abc.Mapping):
   """Map using ModeKeys as keys.
 
   This class creates an immutable mapping from modes to values. For example,
diff --git a/tensorflow/python/saved_model/nested_structure_coder.py b/tensorflow/python/saved_model/nested_structure_coder.py
index 66b02b119d1..0bda4fc2d0d 100644
--- a/tensorflow/python/saved_model/nested_structure_coder.py
+++ b/tensorflow/python/saved_model/nested_structure_coder.py
@@ -39,6 +39,7 @@ from tensorflow.python.framework import dtypes
 from tensorflow.python.framework import tensor_shape
 from tensorflow.python.framework import tensor_spec
 from tensorflow.python.util import compat
+from tensorflow.python.util.compat import collections_abc
 
 
 class NotEncodableError(Exception):
@@ -153,7 +154,7 @@ def _is_named_tuple(instance):
   if not isinstance(instance, tuple):
     return False
   return (hasattr(instance, "_fields") and
-          isinstance(instance._fields, collections.Sequence) and
+          isinstance(instance._fields, collections_abc.Sequence) and
           all(isinstance(f, six.string_types) for f in instance._fields))
 
 
diff --git a/tensorflow/python/saved_model/signature_serialization.py b/tensorflow/python/saved_model/signature_serialization.py
index 0e969e1b43a..3f3725f39c9 100644
--- a/tensorflow/python/saved_model/signature_serialization.py
+++ b/tensorflow/python/saved_model/signature_serialization.py
@@ -18,8 +18,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
-
 from tensorflow.python.eager import def_function
 from tensorflow.python.eager import function as defun
 from tensorflow.python.framework import ops
@@ -29,6 +27,7 @@ from tensorflow.python.saved_model import signature_constants
 from tensorflow.python.training.tracking import base
 from tensorflow.python.util import compat
 from tensorflow.python.util import nest
+from tensorflow.python.util.compat import collections_abc
 
 
 DEFAULT_SIGNATURE_ATTR = "_default_save_signature"
@@ -87,7 +86,7 @@ def canonicalize_signatures(signatures):
   """Converts `signatures` into a dictionary of concrete functions."""
   if signatures is None:
     return {}
-  if not isinstance(signatures, collections.Mapping):
+  if not isinstance(signatures, collections_abc.Mapping):
     signatures = {
         signature_constants.DEFAULT_SERVING_SIGNATURE_DEF_KEY: signatures}
   concrete_signatures = {}
@@ -146,7 +145,7 @@ def _is_flat(sequence):
 
 def _normalize_outputs(outputs, function_name, signature_key):
   """Construct an output dictionary from unnormalized function outputs."""
-  if isinstance(outputs, collections.Mapping):
+  if isinstance(outputs, collections_abc.Mapping):
     for key, value in outputs.items():
       if not isinstance(value, ops.Tensor):
         raise ValueError(
@@ -158,7 +157,7 @@ def _normalize_outputs(outputs, function_name, signature_key):
     return outputs
   else:
     original_outputs = outputs
-    if not isinstance(outputs, collections.Sequence):
+    if not isinstance(outputs, collections_abc.Sequence):
       outputs = [outputs]
     if not _is_flat(outputs):
       raise ValueError(
@@ -180,7 +179,7 @@ def _normalize_outputs(outputs, function_name, signature_key):
 # saved if they contain a _SignatureMap. A ".signatures" attribute containing
 # any other type (e.g. a regular dict) will raise an exception asking the user
 # to first "del obj.signatures" if they want it overwritten.
-class _SignatureMap(collections.Mapping, base.Trackable):
+class _SignatureMap(collections_abc.Mapping, base.Trackable):
   """A collection of SavedModel signatures."""
 
   def __init__(self):
@@ -234,7 +233,7 @@ def create_signature_map(signatures):
     # be more problematic in case future export changes violated these
     # assertions.
     assert isinstance(func, defun.ConcreteFunction)
-    assert isinstance(func.structured_outputs, collections.Mapping)
+    assert isinstance(func.structured_outputs, collections_abc.Mapping)
     # pylint: disable=protected-access
     if len(func._arg_keywords) == 1:
       assert 1 == func._num_positional_args
diff --git a/tensorflow/python/tpu/tpu.py b/tensorflow/python/tpu/tpu.py
index c47b35b59a2..8208b220ebe 100644
--- a/tensorflow/python/tpu/tpu.py
+++ b/tensorflow/python/tpu/tpu.py
@@ -19,7 +19,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 from six.moves import xrange  # pylint: disable=redefined-builtin
 
 from tensorflow.core.framework import attr_value_pb2
@@ -41,6 +40,7 @@ from tensorflow.python.tpu import tpu_function
 from tensorflow.python.tpu.ops import tpu_ops
 from tensorflow.python.util import compat
 from tensorflow.python.util import nest
+from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.tf_export import tf_export
 
 ops.NotDifferentiable("TPUReplicatedInput")
@@ -1022,7 +1022,7 @@ def _postprocess_flat_outputs(outputs):
   if outputs is None:
     outputs = tuple()
   # If the computation only returned one value, makes it a tuple.
-  if not isinstance(outputs, collections.Sequence):
+  if not isinstance(outputs, collections_abc.Sequence):
     outputs = (outputs,)
 
   # Append `no_op` here so that fetching any return value of this function
diff --git a/tensorflow/python/training/input.py b/tensorflow/python/training/input.py
index 21408f3988e..41c8c715d77 100644
--- a/tensorflow/python/training/input.py
+++ b/tensorflow/python/training/input.py
@@ -24,8 +24,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
-
 from six.moves import xrange  # pylint: disable=redefined-builtin
 
 from tensorflow.python.eager import context
@@ -46,6 +44,7 @@ from tensorflow.python.ops import variable_scope as vs
 from tensorflow.python.summary import summary
 from tensorflow.python.training import queue_runner
 from tensorflow.python.util import deprecation
+from tensorflow.python.util.compat import collections_abc
 from tensorflow.python.util.tf_export import tf_export
 
 
@@ -600,7 +599,7 @@ def _store_sparse_tensors_join(tensor_list_list, enqueue_many, keep_input):
 
 def _restore_sparse_tensors(stored_list, sparse_info_list):
   """Restore SparseTensors after dequeue in batch, batch_join, etc."""
-  received_sequence = isinstance(stored_list, collections.Sequence)
+  received_sequence = isinstance(stored_list, collections_abc.Sequence)
   if not received_sequence:
     stored_list = (stored_list,)
   tensors = [
diff --git a/tensorflow/python/training/tracking/data_structures.py b/tensorflow/python/training/tracking/data_structures.py
index b3f5046bfe6..5070b054879 100644
--- a/tensorflow/python/training/tracking/data_structures.py
+++ b/tensorflow/python/training/tracking/data_structures.py
@@ -35,6 +35,7 @@ from tensorflow.python.ops import variables
 from tensorflow.python.saved_model import revived_types
 from tensorflow.python.training.tracking import base
 from tensorflow.python.training.tracking import layer_utils
+from tensorflow.python.util.compat import collections_abc
 
 
 class NoDependency(object):
@@ -249,7 +250,7 @@ class TrackableDataStructure(base.Trackable):
     return self is other
 
 
-class List(TrackableDataStructure, collections.Sequence):
+class List(TrackableDataStructure, collections_abc.Sequence):
   """An append-only sequence type which is trackable.
 
   Maintains checkpoint dependencies on its contents (which must also be
@@ -371,7 +372,7 @@ class List(TrackableDataStructure, collections.Sequence):
 # TODO(tomhennigan) Update to collections.UserList?
 # TODO(allenl): Try switching this to wrapt.ObjectProxy again when we drop
 # Python 3.4 support (may still be tricky).
-class ListWrapper(List, collections.MutableSequence,
+class ListWrapper(List, collections_abc.MutableSequence,
                   # Shadowed, but there for isinstance checks.
                   list):
   """Wraps the built-in `list` to support restore-on-create for variables.
@@ -579,7 +580,7 @@ class ListWrapper(List, collections.MutableSequence,
     }
 
 
-class Mapping(TrackableDataStructure, collections.Mapping):
+class Mapping(TrackableDataStructure, collections_abc.Mapping):
   """An append-only trackable mapping data structure with string keys.
 
   Maintains checkpoint dependencies on its contents (which must also be
diff --git a/tensorflow/python/util/compat.py b/tensorflow/python/util/compat.py
index 76ba91d632f..54d1495ca0c 100644
--- a/tensorflow/python/util/compat.py
+++ b/tensorflow/python/util/compat.py
@@ -38,6 +38,12 @@ import six as _six
 
 from tensorflow.python.util.tf_export import tf_export
 
+try:
+  # This import only works on python 3.3 and above.
+  import collections.abc as collections_abc  # pylint: disable=unused-import
+except ImportError:
+  import collections as collections_abc  # pylint: disable=unused-import
+
 
 def as_bytes(bytes_or_text, encoding='utf-8'):
   """Converts `bytearray`, `bytes`, or unicode python input types to `bytes`.
diff --git a/tensorflow/python/util/nest.py b/tensorflow/python/util/nest.py
index d43720f0ed8..a40d4b1de30 100644
--- a/tensorflow/python/util/nest.py
+++ b/tensorflow/python/util/nest.py
@@ -34,12 +34,11 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections as _collections
-
 import six as _six
 
 from tensorflow.python import pywrap_tensorflow as _pywrap_tensorflow
 from tensorflow.python.util.tf_export import tf_export
+from tensorflow.python.util.compat import collections_abc as _collections_abc
 
 
 _SHALLOW_TREE_HAS_INVALID_KEYS = (
@@ -170,7 +169,7 @@ def _yield_sorted_items(iterable):
   Yields:
     The iterable's (key, value) pairs, in order of sorted keys.
   """
-  if isinstance(iterable, _collections.Mapping):
+  if isinstance(iterable, _collections_abc.Mapping):
     # Iterate through dictionaries in a deterministic order by sorting the
     # keys. Notice this means that we ignore the original order of `OrderedDict`
     # instances. This is intentional, to avoid potential bugs caused by mixing
@@ -205,14 +204,14 @@ is_sequence_or_composite = _pywrap_tensorflow.IsSequenceOrComposite
 
 @tf_export("nest.is_nested")
 def is_nested(seq):
-  """Returns true if its input is a collections.Sequence (except strings).
+  """Returns true if its input is a collections.abc.Sequence (except strings).
 
   Args:
     seq: an input sequence.
 
   Returns:
-    True if the sequence is a not a string and is a collections.Sequence or a
-    dict.
+    True if the sequence is a not a string and is a collections.abc.Sequence
+    or a dict.
   """
   return is_sequence(seq)
 
@@ -344,7 +343,7 @@ def flatten_dict_items(dictionary):
     ValueError: If any key and value do not have the same structure layout, or
     if keys are not unique.
   """
-  if not isinstance(dictionary, (dict, _collections.Mapping)):
+  if not isinstance(dictionary, (dict, _collections_abc.Mapping)):
     raise TypeError("input must be a dictionary")
   flat_dictionary = {}
   for i, v in _six.iteritems(dictionary):
@@ -714,8 +713,8 @@ def assert_shallow_structure(shallow_tree,
             (_is_type_spec(shallow_tree) or _is_type_spec(input_tree))):
         pass  # Compatibility will be checked below.
 
-      elif not (isinstance(shallow_tree, _collections.Mapping)
-                and isinstance(input_tree, _collections.Mapping)):
+      elif not (isinstance(shallow_tree, _collections_abc.Mapping)
+                and isinstance(input_tree, _collections_abc.Mapping)):
         raise TypeError(_STRUCTURES_HAVE_MISMATCHING_TYPES.format(
             input_type=type(input_tree),
             shallow_type=type(shallow_tree)))
@@ -753,7 +752,7 @@ def assert_shallow_structure(shallow_tree,
             _INPUT_TREE_SMALLER_THAN_SHALLOW_TREE.format(
                 input_size=len(input_tree), shallow_size=len(shallow_tree)))
 
-    if isinstance(shallow_tree, _collections.Mapping):
+    if isinstance(shallow_tree, _collections_abc.Mapping):
       absent_keys = set(shallow_tree) - set(input_tree)
       if absent_keys:
         raise ValueError(_SHALLOW_TREE_HAS_INVALID_KEYS
@@ -1315,5 +1314,5 @@ def flatten_with_tuple_paths(structure, expand_composites=False):
                   flatten(structure, expand_composites=expand_composites)))
 
 
-_pywrap_tensorflow.RegisterType("Mapping", _collections.Mapping)
-_pywrap_tensorflow.RegisterType("Sequence", _collections.Sequence)
+_pywrap_tensorflow.RegisterType("Mapping", _collections_abc.Mapping)
+_pywrap_tensorflow.RegisterType("Sequence", _collections_abc.Sequence)
diff --git a/tensorflow/python/util/nest_test.py b/tensorflow/python/util/nest_test.py
index 73cb1788766..854830ffa47 100644
--- a/tensorflow/python/util/nest_test.py
+++ b/tensorflow/python/util/nest_test.py
@@ -32,6 +32,7 @@ from tensorflow.python.ops import array_ops
 from tensorflow.python.ops import math_ops
 from tensorflow.python.platform import test
 from tensorflow.python.util import nest
+from tensorflow.python.util.compat import collections_abc
 
 try:
   import attr  # pylint:disable=g-import-not-at-top
@@ -39,7 +40,7 @@ except ImportError:
   attr = None
 
 
-class _CustomMapping(collections.Mapping):
+class _CustomMapping(collections_abc.Mapping):
 
   def __init__(self, *args, **kwargs):
     self._wrapped = dict(*args, **kwargs)
diff --git a/tensorflow/python/util/object_identity.py b/tensorflow/python/util/object_identity.py
index d4eef5b34b5..aa293f915ea 100644
--- a/tensorflow/python/util/object_identity.py
+++ b/tensorflow/python/util/object_identity.py
@@ -17,9 +17,10 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 import weakref
 
+from tensorflow.python.util.compat import collections_abc
+
 
 class _ObjectIdentityWrapper(object):
   """Wraps an object, mapping __eq__ on wrapper to "is" on wrapped.
@@ -58,7 +59,7 @@ class _WeakObjectIdentityWrapper(_ObjectIdentityWrapper):
     return self._wrapped()
 
 
-class ObjectIdentityDictionary(collections.MutableMapping):
+class ObjectIdentityDictionary(collections_abc.MutableMapping):
   """A mutable mapping data structure which compares using "is".
 
   This is necessary because we have trackable objects (_ListWrapper) which
@@ -109,7 +110,7 @@ class ObjectIdentityWeakKeyDictionary(ObjectIdentityDictionary):
         yield unwrapped
 
 
-class ObjectIdentitySet(collections.MutableSet):
+class ObjectIdentitySet(collections_abc.MutableSet):
   """Like the built-in set, but compares objects with "is"."""
 
   def __init__(self, *args):
diff --git a/tensorflow/python/util/protobuf/compare.py b/tensorflow/python/util/protobuf/compare.py
index 3a3af4bffa5..6331b427e4f 100644
--- a/tensorflow/python/util/protobuf/compare.py
+++ b/tensorflow/python/util/protobuf/compare.py
@@ -62,7 +62,6 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
 import difflib
 
 import six
@@ -72,6 +71,8 @@ from google.protobuf import descriptor_pool
 from google.protobuf import message
 from google.protobuf import text_format
 
+from ..compat import collections_abc
+
 
 def assertProtoEqual(self, a, b, check_initialized=True,  # pylint: disable=invalid-name
                      normalize_numbers=False, msg=None):
@@ -186,7 +187,7 @@ def NormalizeNumberFields(pb):
 
 
 def _IsMap(value):
-  return isinstance(value, collections.Mapping)
+  return isinstance(value, collections_abc.Mapping)
 
 
 def _IsRepeatedContainer(value):
diff --git a/tensorflow/python/util/serialization.py b/tensorflow/python/util/serialization.py
index 2164ba4dbf2..d9335da637f 100644
--- a/tensorflow/python/util/serialization.py
+++ b/tensorflow/python/util/serialization.py
@@ -18,11 +18,10 @@ from __future__ import absolute_import
 from __future__ import division
 from __future__ import print_function
 
-import collections
-
 import numpy as np
 
 from tensorflow.python.framework import tensor_shape
+from tensorflow.python.util.compat import collections_abc
 
 
 def get_json_type(obj):
@@ -63,7 +62,7 @@ def get_json_type(obj):
   if isinstance(obj, tensor_shape.TensorShape):
     return obj.as_list()
 
-  if isinstance(obj, collections.Mapping):
+  if isinstance(obj, collections_abc.Mapping):
     return dict(obj)
 
   raise TypeError('Not JSON Serializable:', obj)